[BOT ISSUE] Anthropic: Server-side tool content blocks (web search, code execution) not decomposed into tool spans #250

Description

@braintrust-bot

Summary

When the Anthropic Messages API returns content blocks from server-side tools (server_tool_use, web_search_tool_result, code_execution_tool_result), the Braintrust wrapper logs them as part of the flat message.content array in the LLM span's output. No child TOOL spans are created for these server-executed tool invocations.

The usage-level metrics for server tools (server_tool_use_web_search_requests, server_tool_use_web_fetch_requests, server_tool_use_code_execution_requests) are properly captured — this gap is specifically about the lack of span-level visibility into individual server-side tool executions and their results.

What is missing

The _log_message_to_span() function (py/src/braintrust/integrations/anthropic/tracing.py, line 490) logs the entire message.content array as a single output blob:

output= {
"role": getattr(message, "role", None),
"content": getattr(message, "content", None), # All content blocks, flat
...
}
span.log(output=output, metrics=metrics, metadata=metadata)

When Anthropic server-side tools are used, message.content contains interleaved blocks like:

Content block typeDescriptionChild TOOL span created?
server_tool_useServer-side tool invocation (search query, code to execute)No
web_search_tool_resultWeb search results with URLs, titles, encrypted contentNo
code_execution_tool_resultCode execution output (stdout, stderr, files)No
text (with citations)Text with citation references to search resultsNo

Each server_tool_use + *_tool_result pair represents a complete server-side tool invocation that could be a child TOOL span with its own input (the query/code), output (the results), and metadata (tool_use_id, error codes).

Comparison with other integrations in this repo

The Google GenAI integration (py/src/braintrust/integrations/google_genai/tracing.py) creates dedicated SpanTypeAttribute.TOOL child spans for equivalent server-side tool outputs:

  • code_execution_call / code_execution_result
  • file_search_call / file_search_result
  • url_context_call / url_context_result
  • mcp_server_tool_call / mcp_server_tool_result

Test coverage

The unit tests in test_anthropic.py validate that server_tool_use metrics are correctly extracted from the usage object (lines 170-282). However, there are no end-to-end tests (or VCR cassettes) that exercise a full server-side tool invocation and verify span-level output. The cassettes/ directory contains no recordings with server_tool_use or web_search_tool_result content blocks.

Braintrust docs status

supported (partial) — The Anthropic integration page documents server_tool_use_* metrics. It does not mention tool span decomposition for server-side tool content blocks.

Upstream sources

Local files inspected

  • py/src/braintrust/integrations/anthropic/tracing.py:
    • _log_message_to_span() (line 490) — logs entire message.content as flat output, no content block type inspection
    • Streaming path uses accumulate_event() then same _log_message_to_span() — same flat treatment
  • py/src/braintrust/integrations/anthropic/_utils.py:
    • extract_anthropic_usage() (line 56) — properly captures server_tool_use metrics (web_search_requests, web_fetch_requests, code_execution_requests)
  • py/src/braintrust/integrations/anthropic/test_anthropic.py — tests validate metrics extraction only; no end-to-end cassettes for server-side tools
  • py/src/braintrust/integrations/anthropic/cassettes/ — no cassettes with server-side tool content blocks
  • py/src/braintrust/integrations/google_genai/tracing.py (lines 771-838) — creates SpanTypeAttribute.TOOL child spans for equivalent tool outputs (for comparison)

Metadata

Metadata

Projects

No projects

    Milestone

    No milestone

    Relationships

    None yet

    Development

    No branches or pull requests

    Issue actions

    , 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all
     blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
    }
    } catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
    })();
    (function(){
    try {
    var __m = "github.com";
    var __re = new RegExp('^' + "github\\.com" + '
    
    Skip to content

    [BOT ISSUE] Anthropic: Server-side tool content blocks (web search, code execution) not decomposed into tool spans #250

    Description

    @braintrust-bot

    Summary

    When the Anthropic Messages API returns content blocks from server-side tools (server_tool_use, web_search_tool_result, code_execution_tool_result), the Braintrust wrapper logs them as part of the flat message.content array in the LLM span's output. No child TOOL spans are created for these server-executed tool invocations.

    The usage-level metrics for server tools (server_tool_use_web_search_requests, server_tool_use_web_fetch_requests, server_tool_use_code_execution_requests) are properly captured — this gap is specifically about the lack of span-level visibility into individual server-side tool executions and their results.

    What is missing

    The _log_message_to_span() function (py/src/braintrust/integrations/anthropic/tracing.py, line 490) logs the entire message.content array as a single output blob:

    output= {
    "role": getattr(message, "role", None),
    "content": getattr(message, "content", None), # All content blocks, flat
    ...
    }
    span.log(output=output, metrics=metrics, metadata=metadata)

    When Anthropic server-side tools are used, message.content contains interleaved blocks like:

    Content block typeDescriptionChild TOOL span created?
    server_tool_useServer-side tool invocation (search query, code to execute)No
    web_search_tool_resultWeb search results with URLs, titles, encrypted contentNo
    code_execution_tool_resultCode execution output (stdout, stderr, files)No
    text (with citations)Text with citation references to search resultsNo

    Each server_tool_use + *_tool_result pair represents a complete server-side tool invocation that could be a child TOOL span with its own input (the query/code), output (the results), and metadata (tool_use_id, error codes).

    Comparison with other integrations in this repo

    The Google GenAI integration (py/src/braintrust/integrations/google_genai/tracing.py) creates dedicated SpanTypeAttribute.TOOL child spans for equivalent server-side tool outputs:

    • code_execution_call / code_execution_result
    • file_search_call / file_search_result
    • url_context_call / url_context_result
    • mcp_server_tool_call / mcp_server_tool_result

    Test coverage

    The unit tests in test_anthropic.py validate that server_tool_use metrics are correctly extracted from the usage object (lines 170-282). However, there are no end-to-end tests (or VCR cassettes) that exercise a full server-side tool invocation and verify span-level output. The cassettes/ directory contains no recordings with server_tool_use or web_search_tool_result content blocks.

    Braintrust docs status

    supported (partial) — The Anthropic integration page documents server_tool_use_* metrics. It does not mention tool span decomposition for server-side tool content blocks.

    Upstream sources

    Local files inspected

    • py/src/braintrust/integrations/anthropic/tracing.py:
      • _log_message_to_span() (line 490) — logs entire message.content as flat output, no content block type inspection
      • Streaming path uses accumulate_event() then same _log_message_to_span() — same flat treatment
    • py/src/braintrust/integrations/anthropic/_utils.py:
      • extract_anthropic_usage() (line 56) — properly captures server_tool_use metrics (web_search_requests, web_fetch_requests, code_execution_requests)
    • py/src/braintrust/integrations/anthropic/test_anthropic.py — tests validate metrics extraction only; no end-to-end cassettes for server-side tools
    • py/src/braintrust/integrations/anthropic/cassettes/ — no cassettes with server-side tool content blocks
    • py/src/braintrust/integrations/google_genai/tracing.py (lines 771-838) — creates SpanTypeAttribute.TOOL child spans for equivalent tool outputs (for comparison)

    Metadata

    Metadata

    Projects

    No projects

      Milestone

      No milestone

      Relationships

      None yet

      Development

      No branches or pull requests

      Issue actions

      , 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix"); } } catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
      Skip to content

      [BOT ISSUE] Anthropic: Server-side tool content blocks (web search, code execution) not decomposed into tool spans #250

      Description

      @braintrust-bot

      Summary

      When the Anthropic Messages API returns content blocks from server-side tools (server_tool_use, web_search_tool_result, code_execution_tool_result), the Braintrust wrapper logs them as part of the flat message.content array in the LLM span's output. No child TOOL spans are created for these server-executed tool invocations.

      The usage-level metrics for server tools (server_tool_use_web_search_requests, server_tool_use_web_fetch_requests, server_tool_use_code_execution_requests) are properly captured — this gap is specifically about the lack of span-level visibility into individual server-side tool executions and their results.

      What is missing

      The _log_message_to_span() function (py/src/braintrust/integrations/anthropic/tracing.py, line 490) logs the entire message.content array as a single output blob:

      output= {
      "role": getattr(message, "role", None),
      "content": getattr(message, "content", None), # All content blocks, flat
      ...
      }
      span.log(output=output, metrics=metrics, metadata=metadata)

      When Anthropic server-side tools are used, message.content contains interleaved blocks like:

      Content block typeDescriptionChild TOOL span created?
      server_tool_useServer-side tool invocation (search query, code to execute)No
      web_search_tool_resultWeb search results with URLs, titles, encrypted contentNo
      code_execution_tool_resultCode execution output (stdout, stderr, files)No
      text (with citations)Text with citation references to search resultsNo

      Each server_tool_use + *_tool_result pair represents a complete server-side tool invocation that could be a child TOOL span with its own input (the query/code), output (the results), and metadata (tool_use_id, error codes).

      Comparison with other integrations in this repo

      The Google GenAI integration (py/src/braintrust/integrations/google_genai/tracing.py) creates dedicated SpanTypeAttribute.TOOL child spans for equivalent server-side tool outputs:

      • code_execution_call / code_execution_result
      • file_search_call / file_search_result
      • url_context_call / url_context_result
      • mcp_server_tool_call / mcp_server_tool_result

      Test coverage

      The unit tests in test_anthropic.py validate that server_tool_use metrics are correctly extracted from the usage object (lines 170-282). However, there are no end-to-end tests (or VCR cassettes) that exercise a full server-side tool invocation and verify span-level output. The cassettes/ directory contains no recordings with server_tool_use or web_search_tool_result content blocks.

      Braintrust docs status

      supported (partial) — The Anthropic integration page documents server_tool_use_* metrics. It does not mention tool span decomposition for server-side tool content blocks.

      Upstream sources

      Local files inspected

      • py/src/braintrust/integrations/anthropic/tracing.py:
        • _log_message_to_span() (line 490) — logs entire message.content as flat output, no content block type inspection
        • Streaming path uses accumulate_event() then same _log_message_to_span() — same flat treatment
      • py/src/braintrust/integrations/anthropic/_utils.py:
        • extract_anthropic_usage() (line 56) — properly captures server_tool_use metrics (web_search_requests, web_fetch_requests, code_execution_requests)
      • py/src/braintrust/integrations/anthropic/test_anthropic.py — tests validate metrics extraction only; no end-to-end cassettes for server-side tools
      • py/src/braintrust/integrations/anthropic/cassettes/ — no cassettes with server-side tool content blocks
      • py/src/braintrust/integrations/google_genai/tracing.py (lines 771-838) — creates SpanTypeAttribute.TOOL child spans for equivalent tool outputs (for comparison)

      Metadata

      Metadata

      Projects

      No projects

        Milestone

        No milestone

        Relationships

        None yet

        Development

        No branches or pull requests

        Issue actions

        , 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms"); } } catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
        Skip to content

        [BOT ISSUE] Anthropic: Server-side tool content blocks (web search, code execution) not decomposed into tool spans #250

        Description

        @braintrust-bot

        Summary

        When the Anthropic Messages API returns content blocks from server-side tools (server_tool_use, web_search_tool_result, code_execution_tool_result), the Braintrust wrapper logs them as part of the flat message.content array in the LLM span's output. No child TOOL spans are created for these server-executed tool invocations.

        The usage-level metrics for server tools (server_tool_use_web_search_requests, server_tool_use_web_fetch_requests, server_tool_use_code_execution_requests) are properly captured — this gap is specifically about the lack of span-level visibility into individual server-side tool executions and their results.

        What is missing

        The _log_message_to_span() function (py/src/braintrust/integrations/anthropic/tracing.py, line 490) logs the entire message.content array as a single output blob:

        output= {
        "role": getattr(message, "role", None),
        "content": getattr(message, "content", None), # All content blocks, flat
        ...
        }
        span.log(output=output, metrics=metrics, metadata=metadata)

        When Anthropic server-side tools are used, message.content contains interleaved blocks like:

        Content block typeDescriptionChild TOOL span created?
        server_tool_useServer-side tool invocation (search query, code to execute)No
        web_search_tool_resultWeb search results with URLs, titles, encrypted contentNo
        code_execution_tool_resultCode execution output (stdout, stderr, files)No
        text (with citations)Text with citation references to search resultsNo

        Each server_tool_use + *_tool_result pair represents a complete server-side tool invocation that could be a child TOOL span with its own input (the query/code), output (the results), and metadata (tool_use_id, error codes).

        Comparison with other integrations in this repo

        The Google GenAI integration (py/src/braintrust/integrations/google_genai/tracing.py) creates dedicated SpanTypeAttribute.TOOL child spans for equivalent server-side tool outputs:

        • code_execution_call / code_execution_result
        • file_search_call / file_search_result
        • url_context_call / url_context_result
        • mcp_server_tool_call / mcp_server_tool_result

        Test coverage

        The unit tests in test_anthropic.py validate that server_tool_use metrics are correctly extracted from the usage object (lines 170-282). However, there are no end-to-end tests (or VCR cassettes) that exercise a full server-side tool invocation and verify span-level output. The cassettes/ directory contains no recordings with server_tool_use or web_search_tool_result content blocks.

        Braintrust docs status

        supported (partial) — The Anthropic integration page documents server_tool_use_* metrics. It does not mention tool span decomposition for server-side tool content blocks.

        Upstream sources

        Local files inspected

        • py/src/braintrust/integrations/anthropic/tracing.py:
          • _log_message_to_span() (line 490) — logs entire message.content as flat output, no content block type inspection
          • Streaming path uses accumulate_event() then same _log_message_to_span() — same flat treatment
        • py/src/braintrust/integrations/anthropic/_utils.py:
          • extract_anthropic_usage() (line 56) — properly captures server_tool_use metrics (web_search_requests, web_fetch_requests, code_execution_requests)
        • py/src/braintrust/integrations/anthropic/test_anthropic.py — tests validate metrics extraction only; no end-to-end cassettes for server-side tools
        • py/src/braintrust/integrations/anthropic/cassettes/ — no cassettes with server-side tool content blocks
        • py/src/braintrust/integrations/google_genai/tracing.py (lines 771-838) — creates SpanTypeAttribute.TOOL child spans for equivalent tool outputs (for comparison)

        Metadata

        Metadata

        Projects

        No projects

          Milestone

          No milestone

          Relationships

          None yet

          Development

          No branches or pull requests

          Issue actions

          , 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links"); } } catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); } })(); (function(){ try { var __m = "youtube.com"; var __re = new RegExp('^' + "youtube\\.com" + '
          Skip to content

          [BOT ISSUE] Anthropic: Server-side tool content blocks (web search, code execution) not decomposed into tool spans #250

          Description

          @braintrust-bot

          Summary

          When the Anthropic Messages API returns content blocks from server-side tools (server_tool_use, web_search_tool_result, code_execution_tool_result), the Braintrust wrapper logs them as part of the flat message.content array in the LLM span's output. No child TOOL spans are created for these server-executed tool invocations.

          The usage-level metrics for server tools (server_tool_use_web_search_requests, server_tool_use_web_fetch_requests, server_tool_use_code_execution_requests) are properly captured — this gap is specifically about the lack of span-level visibility into individual server-side tool executions and their results.

          What is missing

          The _log_message_to_span() function (py/src/braintrust/integrations/anthropic/tracing.py, line 490) logs the entire message.content array as a single output blob:

          output= {
          "role": getattr(message, "role", None),
          "content": getattr(message, "content", None), # All content blocks, flat
          ...
          }
          span.log(output=output, metrics=metrics, metadata=metadata)

          When Anthropic server-side tools are used, message.content contains interleaved blocks like:

          Content block typeDescriptionChild TOOL span created?
          server_tool_useServer-side tool invocation (search query, code to execute)No
          web_search_tool_resultWeb search results with URLs, titles, encrypted contentNo
          code_execution_tool_resultCode execution output (stdout, stderr, files)No
          text (with citations)Text with citation references to search resultsNo

          Each server_tool_use + *_tool_result pair represents a complete server-side tool invocation that could be a child TOOL span with its own input (the query/code), output (the results), and metadata (tool_use_id, error codes).

          Comparison with other integrations in this repo

          The Google GenAI integration (py/src/braintrust/integrations/google_genai/tracing.py) creates dedicated SpanTypeAttribute.TOOL child spans for equivalent server-side tool outputs:

          • code_execution_call / code_execution_result
          • file_search_call / file_search_result
          • url_context_call / url_context_result
          • mcp_server_tool_call / mcp_server_tool_result

          Test coverage

          The unit tests in test_anthropic.py validate that server_tool_use metrics are correctly extracted from the usage object (lines 170-282). However, there are no end-to-end tests (or VCR cassettes) that exercise a full server-side tool invocation and verify span-level output. The cassettes/ directory contains no recordings with server_tool_use or web_search_tool_result content blocks.

          Braintrust docs status

          supported (partial) — The Anthropic integration page documents server_tool_use_* metrics. It does not mention tool span decomposition for server-side tool content blocks.

          Upstream sources

          Local files inspected

          • py/src/braintrust/integrations/anthropic/tracing.py:
            • _log_message_to_span() (line 490) — logs entire message.content as flat output, no content block type inspection
            • Streaming path uses accumulate_event() then same _log_message_to_span() — same flat treatment
          • py/src/braintrust/integrations/anthropic/_utils.py:
            • extract_anthropic_usage() (line 56) — properly captures server_tool_use metrics (web_search_requests, web_fetch_requests, code_execution_requests)
          • py/src/braintrust/integrations/anthropic/test_anthropic.py — tests validate metrics extraction only; no end-to-end cassettes for server-side tools
          • py/src/braintrust/integrations/anthropic/cassettes/ — no cassettes with server-side tool content blocks
          • py/src/braintrust/integrations/google_genai/tracing.py (lines 771-838) — creates SpanTypeAttribute.TOOL child spans for equivalent tool outputs (for comparison)

          Metadata

          Metadata

          Projects

          No projects

            Milestone

            No milestone

            Relationships

            None yet

            Development

            No branches or pull requests

            Issue actions

            , 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default"); } } catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
            Skip to content

            [BOT ISSUE] Anthropic: Server-side tool content blocks (web search, code execution) not decomposed into tool spans #250

            Description

            @braintrust-bot

            Summary

            When the Anthropic Messages API returns content blocks from server-side tools (server_tool_use, web_search_tool_result, code_execution_tool_result), the Braintrust wrapper logs them as part of the flat message.content array in the LLM span's output. No child TOOL spans are created for these server-executed tool invocations.

            The usage-level metrics for server tools (server_tool_use_web_search_requests, server_tool_use_web_fetch_requests, server_tool_use_code_execution_requests) are properly captured — this gap is specifically about the lack of span-level visibility into individual server-side tool executions and their results.

            What is missing

            The _log_message_to_span() function (py/src/braintrust/integrations/anthropic/tracing.py, line 490) logs the entire message.content array as a single output blob:

            output= {
            "role": getattr(message, "role", None),
            "content": getattr(message, "content", None), # All content blocks, flat
            ...
            }
            span.log(output=output, metrics=metrics, metadata=metadata)

            When Anthropic server-side tools are used, message.content contains interleaved blocks like:

            Content block typeDescriptionChild TOOL span created?
            server_tool_useServer-side tool invocation (search query, code to execute)No
            web_search_tool_resultWeb search results with URLs, titles, encrypted contentNo
            code_execution_tool_resultCode execution output (stdout, stderr, files)No
            text (with citations)Text with citation references to search resultsNo

            Each server_tool_use + *_tool_result pair represents a complete server-side tool invocation that could be a child TOOL span with its own input (the query/code), output (the results), and metadata (tool_use_id, error codes).

            Comparison with other integrations in this repo

            The Google GenAI integration (py/src/braintrust/integrations/google_genai/tracing.py) creates dedicated SpanTypeAttribute.TOOL child spans for equivalent server-side tool outputs:

            • code_execution_call / code_execution_result
            • file_search_call / file_search_result
            • url_context_call / url_context_result
            • mcp_server_tool_call / mcp_server_tool_result

            Test coverage

            The unit tests in test_anthropic.py validate that server_tool_use metrics are correctly extracted from the usage object (lines 170-282). However, there are no end-to-end tests (or VCR cassettes) that exercise a full server-side tool invocation and verify span-level output. The cassettes/ directory contains no recordings with server_tool_use or web_search_tool_result content blocks.

            Braintrust docs status

            supported (partial) — The Anthropic integration page documents server_tool_use_* metrics. It does not mention tool span decomposition for server-side tool content blocks.

            Upstream sources

            Local files inspected

            • py/src/braintrust/integrations/anthropic/tracing.py:
              • _log_message_to_span() (line 490) — logs entire message.content as flat output, no content block type inspection
              • Streaming path uses accumulate_event() then same _log_message_to_span() — same flat treatment
            • py/src/braintrust/integrations/anthropic/_utils.py:
              • extract_anthropic_usage() (line 56) — properly captures server_tool_use metrics (web_search_requests, web_fetch_requests, code_execution_requests)
            • py/src/braintrust/integrations/anthropic/test_anthropic.py — tests validate metrics extraction only; no end-to-end cassettes for server-side tools
            • py/src/braintrust/integrations/anthropic/cassettes/ — no cassettes with server-side tool content blocks
            • py/src/braintrust/integrations/google_genai/tracing.py (lines 771-838) — creates SpanTypeAttribute.TOOL child spans for equivalent tool outputs (for comparison)

            Metadata

            Metadata

            Projects

            No projects

              Milestone

              No milestone

              Relationships

              None yet

              Development

              No branches or pull requests

              Issue actions

              , 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers"); } } catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
              Skip to content

              [BOT ISSUE] Anthropic: Server-side tool content blocks (web search, code execution) not decomposed into tool spans #250

              Description

              @braintrust-bot

              Summary

              When the Anthropic Messages API returns content blocks from server-side tools (server_tool_use, web_search_tool_result, code_execution_tool_result), the Braintrust wrapper logs them as part of the flat message.content array in the LLM span's output. No child TOOL spans are created for these server-executed tool invocations.

              The usage-level metrics for server tools (server_tool_use_web_search_requests, server_tool_use_web_fetch_requests, server_tool_use_code_execution_requests) are properly captured — this gap is specifically about the lack of span-level visibility into individual server-side tool executions and their results.

              What is missing

              The _log_message_to_span() function (py/src/braintrust/integrations/anthropic/tracing.py, line 490) logs the entire message.content array as a single output blob:

              output= {
              "role": getattr(message, "role", None),
              "content": getattr(message, "content", None), # All content blocks, flat
              ...
              }
              span.log(output=output, metrics=metrics, metadata=metadata)

              When Anthropic server-side tools are used, message.content contains interleaved blocks like:

              Content block typeDescriptionChild TOOL span created?
              server_tool_useServer-side tool invocation (search query, code to execute)No
              web_search_tool_resultWeb search results with URLs, titles, encrypted contentNo
              code_execution_tool_resultCode execution output (stdout, stderr, files)No
              text (with citations)Text with citation references to search resultsNo

              Each server_tool_use + *_tool_result pair represents a complete server-side tool invocation that could be a child TOOL span with its own input (the query/code), output (the results), and metadata (tool_use_id, error codes).

              Comparison with other integrations in this repo

              The Google GenAI integration (py/src/braintrust/integrations/google_genai/tracing.py) creates dedicated SpanTypeAttribute.TOOL child spans for equivalent server-side tool outputs:

              • code_execution_call / code_execution_result
              • file_search_call / file_search_result
              • url_context_call / url_context_result
              • mcp_server_tool_call / mcp_server_tool_result

              Test coverage

              The unit tests in test_anthropic.py validate that server_tool_use metrics are correctly extracted from the usage object (lines 170-282). However, there are no end-to-end tests (or VCR cassettes) that exercise a full server-side tool invocation and verify span-level output. The cassettes/ directory contains no recordings with server_tool_use or web_search_tool_result content blocks.

              Braintrust docs status

              supported (partial) — The Anthropic integration page documents server_tool_use_* metrics. It does not mention tool span decomposition for server-side tool content blocks.

              Upstream sources

              Local files inspected

              • py/src/braintrust/integrations/anthropic/tracing.py:
                • _log_message_to_span() (line 490) — logs entire message.content as flat output, no content block type inspection
                • Streaming path uses accumulate_event() then same _log_message_to_span() — same flat treatment
              • py/src/braintrust/integrations/anthropic/_utils.py:
                • extract_anthropic_usage() (line 56) — properly captures server_tool_use metrics (web_search_requests, web_fetch_requests, code_execution_requests)
              • py/src/braintrust/integrations/anthropic/test_anthropic.py — tests validate metrics extraction only; no end-to-end cassettes for server-side tools
              • py/src/braintrust/integrations/anthropic/cassettes/ — no cassettes with server-side tool content blocks
              • py/src/braintrust/integrations/google_genai/tracing.py (lines 771-838) — creates SpanTypeAttribute.TOOL child spans for equivalent tool outputs (for comparison)

              Metadata

              Metadata

              Projects

              No projects

                Milestone

                No milestone

                Relationships

                None yet

                Development

                No branches or pull requests

                Issue actions

                , 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode"); } } catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); } })(); })();
                Skip to content

                [BOT ISSUE] Anthropic: Server-side tool content blocks (web search, code execution) not decomposed into tool spans #250

                Description

                @braintrust-bot

                Summary

                When the Anthropic Messages API returns content blocks from server-side tools (server_tool_use, web_search_tool_result, code_execution_tool_result), the Braintrust wrapper logs them as part of the flat message.content array in the LLM span's output. No child TOOL spans are created for these server-executed tool invocations.

                The usage-level metrics for server tools (server_tool_use_web_search_requests, server_tool_use_web_fetch_requests, server_tool_use_code_execution_requests) are properly captured — this gap is specifically about the lack of span-level visibility into individual server-side tool executions and their results.

                What is missing

                The _log_message_to_span() function (py/src/braintrust/integrations/anthropic/tracing.py, line 490) logs the entire message.content array as a single output blob:

                output= {
                "role": getattr(message, "role", None),
                "content": getattr(message, "content", None), # All content blocks, flat
                ...
                }
                span.log(output=output, metrics=metrics, metadata=metadata)

                When Anthropic server-side tools are used, message.content contains interleaved blocks like:

                Content block typeDescriptionChild TOOL span created?
                server_tool_useServer-side tool invocation (search query, code to execute)No
                web_search_tool_resultWeb search results with URLs, titles, encrypted contentNo
                code_execution_tool_resultCode execution output (stdout, stderr, files)No
                text (with citations)Text with citation references to search resultsNo

                Each server_tool_use + *_tool_result pair represents a complete server-side tool invocation that could be a child TOOL span with its own input (the query/code), output (the results), and metadata (tool_use_id, error codes).

                Comparison with other integrations in this repo

                The Google GenAI integration (py/src/braintrust/integrations/google_genai/tracing.py) creates dedicated SpanTypeAttribute.TOOL child spans for equivalent server-side tool outputs:

                • code_execution_call / code_execution_result
                • file_search_call / file_search_result
                • url_context_call / url_context_result
                • mcp_server_tool_call / mcp_server_tool_result

                Test coverage

                The unit tests in test_anthropic.py validate that server_tool_use metrics are correctly extracted from the usage object (lines 170-282). However, there are no end-to-end tests (or VCR cassettes) that exercise a full server-side tool invocation and verify span-level output. The cassettes/ directory contains no recordings with server_tool_use or web_search_tool_result content blocks.

                Braintrust docs status

                supported (partial) — The Anthropic integration page documents server_tool_use_* metrics. It does not mention tool span decomposition for server-side tool content blocks.

                Upstream sources

                Local files inspected

                • py/src/braintrust/integrations/anthropic/tracing.py:
                  • _log_message_to_span() (line 490) — logs entire message.content as flat output, no content block type inspection
                  • Streaming path uses accumulate_event() then same _log_message_to_span() — same flat treatment
                • py/src/braintrust/integrations/anthropic/_utils.py:
                  • extract_anthropic_usage() (line 56) — properly captures server_tool_use metrics (web_search_requests, web_fetch_requests, code_execution_requests)
                • py/src/braintrust/integrations/anthropic/test_anthropic.py — tests validate metrics extraction only; no end-to-end cassettes for server-side tools
                • py/src/braintrust/integrations/anthropic/cassettes/ — no cassettes with server-side tool content blocks
                • py/src/braintrust/integrations/google_genai/tracing.py (lines 771-838) — creates SpanTypeAttribute.TOOL child spans for equivalent tool outputs (for comparison)

                Metadata

                Metadata

                Projects

                No projects

                  Milestone

                  No milestone

                  Relationships

                  None yet

                  Development

                  No branches or pull requests

                  Issue actions