[feat] Evaluate rlmgrep for terraphim-ai codebase search #871

Open
Open
[feat] Evaluate rlmgrep for terraphim-ai codebase search#871

Description

@AlexMikhalev
AlexMikhalev
opened on May 16, 2026

Context

rlmgrep (github.com/halfprice06/rlmgrep) is a grep-shaped CLI search tool powered by DSPy's RLM (Refined Language Model). It accepts natural-language queries and returns matches in grep-like format, with full visibility into the RLM's reasoning loop (via rlmgrep -v).

Relevant signal: Alex has liked and bookmarked the rlmgrep launch tweet, indicating strong interest in RLM-based search for codebases.

Problem Statement

Current codebase search tools (grep, ripgrep, gtr for issue triage) operate on text/regex patterns. RLM-based search could:

  1. Answer natural-language questions about the codebase — Where is retry/backoff configured and what are the defaults? — and return the actual source lines in grep format
  2. Understand semantic intent — e.g. find the error handling around the gitea API calls without needing to know the exact function names
  3. Expose the RLM reasoning trace — rlmgrep -v shows iteration-by-iteration reasoning, which is audit-worthy for AI-assisted toolchains

Evaluation Criteria

  • Install rlmgrep: uv tool install --python 3.11 rlmgrep
  • Run against terraphim-ai Rust codebase — test semantic queries about error handling, executor selection, RLM hook invocation
  • Run against terraphim/terraphim-skills skill definitions — test natural-language skill discovery
  • Compare output quality vs grep -r and gtr for the same queries
  • Evaluate --answer mode for generating code answers grounded in actual source
  • Assess whether the verbose RLM trace (-v) is useful for agent audit trails
  • Document findings in .docs/rlmgrep-evaluation.md

rlmgrep Key Features to Test

FeatureWhat to test
--answerNatural-language code Q&A with citations
-C NContext lines in grep format
-v verboseFull RLM iteration traces
PDF/Office supportSkill docs in .docs/
Multi-providerOpenAI vs Anthropic vs Gemini outputs
Sidecar cachingImage/audio description caching

References

  • rlmgrep repo: github.com/halfprice06/rlmgrep
  • Author: @gooby_esq (Daniel Price)
  • Install: uv tool install --python 3.11 rlmgrep
  • RLM concept: DSPy RLM — LLM that generates code to fetch information, then reasons over results before submitting

Labels

feature/evaluation, AI/RLM, good-first-issue

Priority

P2 — informational/value assessment before committing any integration work.

Activity

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      , '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
      [feat] Evaluate rlmgrep for terraphim-ai codebase search #871
      Open
      Open
      [feat] Evaluate rlmgrep for terraphim-ai codebase search#871
      Description
      @AlexMikhalev
      AlexMikhalev
      opened on May 16, 2026
      Context
      rlmgrep (github.com/halfprice06/rlmgrep) is a grep-shaped CLI search tool powered by DSPy's RLM (Refined Language Model). It accepts natural-language queries and returns matches in grep-like format, with full visibility into the RLM's reasoning loop (via rlmgrep -v).
      Relevant signal: Alex has liked and bookmarked the rlmgrep launch tweet, indicating strong interest in RLM-based search for codebases.
      Problem Statement
      Current codebase search tools (grep, ripgrep, gtr for issue triage) operate on text/regex patterns. RLM-based search could:
      1. Answer natural-language questions about the codebase — Where is retry/backoff configured and what are the defaults? — and return the actual source lines in grep format
      2. Understand semantic intent — e.g. find the error handling around the gitea API calls without needing to know the exact function names
      3. Expose the RLM reasoning trace — rlmgrep -v shows iteration-by-iteration reasoning, which is audit-worthy for AI-assisted toolchains
      Evaluation Criteria
      •  Install rlmgrep: uv tool install --python 3.11 rlmgrep
      •  Run against terraphim-ai Rust codebase — test semantic queries about error handling, executor selection, RLM hook invocation
      •  Run against terraphim/terraphim-skills skill definitions — test natural-language skill discovery
      •  Compare output quality vs grep -r and gtr for the same queries
      •  Evaluate --answer mode for generating code answers grounded in actual source
      •  Assess whether the verbose RLM trace (-v) is useful for agent audit trails
      •  Document findings in .docs/rlmgrep-evaluation.md
      rlmgrep Key Features to Test
      FeatureWhat to test
      --answerNatural-language code Q&A with citations
      -C NContext lines in grep format
      -v verboseFull RLM iteration traces
      PDF/Office supportSkill docs in .docs/
      Multi-providerOpenAI vs Anthropic vs Gemini outputs
      Sidecar cachingImage/audio description caching
      References
      • rlmgrep repo: github.com/halfprice06/rlmgrep
      • Author: @gooby_esq (Daniel Price)
      • Install: uv tool install --python 3.11 rlmgrep
      • RLM concept: DSPy RLM — LLM that generates code to fetch information, then reasons over results before submitting
      Labels
      feature/evaluation, AI/RLM, good-first-issue
      Priority
      P2 — informational/value assessment before committing any integration work.
      Activity
      Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
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, '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
          [feat] Evaluate rlmgrep for terraphim-ai codebase search #871
          Open
          Open
          [feat] Evaluate rlmgrep for terraphim-ai codebase search#871
          Description
          @AlexMikhalev
          AlexMikhalev
          opened on May 16, 2026
          Context
          rlmgrep (github.com/halfprice06/rlmgrep) is a grep-shaped CLI search tool powered by DSPy's RLM (Refined Language Model). It accepts natural-language queries and returns matches in grep-like format, with full visibility into the RLM's reasoning loop (via rlmgrep -v).
          Relevant signal: Alex has liked and bookmarked the rlmgrep launch tweet, indicating strong interest in RLM-based search for codebases.
          Problem Statement
          Current codebase search tools (grep, ripgrep, gtr for issue triage) operate on text/regex patterns. RLM-based search could:
          1. Answer natural-language questions about the codebase — Where is retry/backoff configured and what are the defaults? — and return the actual source lines in grep format
          2. Understand semantic intent — e.g. find the error handling around the gitea API calls without needing to know the exact function names
          3. Expose the RLM reasoning trace — rlmgrep -v shows iteration-by-iteration reasoning, which is audit-worthy for AI-assisted toolchains
          Evaluation Criteria
          •  Install rlmgrep: uv tool install --python 3.11 rlmgrep
          •  Run against terraphim-ai Rust codebase — test semantic queries about error handling, executor selection, RLM hook invocation
          •  Run against terraphim/terraphim-skills skill definitions — test natural-language skill discovery
          •  Compare output quality vs grep -r and gtr for the same queries
          •  Evaluate --answer mode for generating code answers grounded in actual source
          •  Assess whether the verbose RLM trace (-v) is useful for agent audit trails
          •  Document findings in .docs/rlmgrep-evaluation.md
          rlmgrep Key Features to Test
          FeatureWhat to test
          --answerNatural-language code Q&A with citations
          -C NContext lines in grep format
          -v verboseFull RLM iteration traces
          PDF/Office supportSkill docs in .docs/
          Multi-providerOpenAI vs Anthropic vs Gemini outputs
          Sidecar cachingImage/audio description caching
          References
          • rlmgrep repo: github.com/halfprice06/rlmgrep
          • Author: @gooby_esq (Daniel Price)
          • Install: uv tool install --python 3.11 rlmgrep
          • RLM concept: DSPy RLM — LLM that generates code to fetch information, then reasons over results before submitting
          Labels
          feature/evaluation, AI/RLM, good-first-issue
          Priority
          P2 — informational/value assessment before committing any integration work.
          Activity
          Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
          Metadata
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, '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
              [feat] Evaluate rlmgrep for terraphim-ai codebase search #871
              Open
              Open
              [feat] Evaluate rlmgrep for terraphim-ai codebase search#871
              Description
              @AlexMikhalev
              AlexMikhalev
              opened on May 16, 2026
              Context
              rlmgrep (github.com/halfprice06/rlmgrep) is a grep-shaped CLI search tool powered by DSPy's RLM (Refined Language Model). It accepts natural-language queries and returns matches in grep-like format, with full visibility into the RLM's reasoning loop (via rlmgrep -v).
              Relevant signal: Alex has liked and bookmarked the rlmgrep launch tweet, indicating strong interest in RLM-based search for codebases.
              Problem Statement
              Current codebase search tools (grep, ripgrep, gtr for issue triage) operate on text/regex patterns. RLM-based search could:
              1. Answer natural-language questions about the codebase — Where is retry/backoff configured and what are the defaults? — and return the actual source lines in grep format
              2. Understand semantic intent — e.g. find the error handling around the gitea API calls without needing to know the exact function names
              3. Expose the RLM reasoning trace — rlmgrep -v shows iteration-by-iteration reasoning, which is audit-worthy for AI-assisted toolchains
              Evaluation Criteria
              •  Install rlmgrep: uv tool install --python 3.11 rlmgrep
              •  Run against terraphim-ai Rust codebase — test semantic queries about error handling, executor selection, RLM hook invocation
              •  Run against terraphim/terraphim-skills skill definitions — test natural-language skill discovery
              •  Compare output quality vs grep -r and gtr for the same queries
              •  Evaluate --answer mode for generating code answers grounded in actual source
              •  Assess whether the verbose RLM trace (-v) is useful for agent audit trails
              •  Document findings in .docs/rlmgrep-evaluation.md
              rlmgrep Key Features to Test
              FeatureWhat to test
              --answerNatural-language code Q&A with citations
              -C NContext lines in grep format
              -v verboseFull RLM iteration traces
              PDF/Office supportSkill docs in .docs/
              Multi-providerOpenAI vs Anthropic vs Gemini outputs
              Sidecar cachingImage/audio description caching
              References
              • rlmgrep repo: github.com/halfprice06/rlmgrep
              • Author: @gooby_esq (Daniel Price)
              • Install: uv tool install --python 3.11 rlmgrep
              • RLM concept: DSPy RLM — LLM that generates code to fetch information, then reasons over results before submitting
              Labels
              feature/evaluation, AI/RLM, good-first-issue
              Priority
              P2 — informational/value assessment before committing any integration work.
              Activity
              Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
              Metadata
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                Labels
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, '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
                  [feat] Evaluate rlmgrep for terraphim-ai codebase search #871
                  Open
                  Open
                  [feat] Evaluate rlmgrep for terraphim-ai codebase search#871
                  Description
                  @AlexMikhalev
                  AlexMikhalev
                  opened on May 16, 2026
                  Context
                  rlmgrep (github.com/halfprice06/rlmgrep) is a grep-shaped CLI search tool powered by DSPy's RLM (Refined Language Model). It accepts natural-language queries and returns matches in grep-like format, with full visibility into the RLM's reasoning loop (via rlmgrep -v).
                  Relevant signal: Alex has liked and bookmarked the rlmgrep launch tweet, indicating strong interest in RLM-based search for codebases.
                  Problem Statement
                  Current codebase search tools (grep, ripgrep, gtr for issue triage) operate on text/regex patterns. RLM-based search could:
                  1. Answer natural-language questions about the codebase — Where is retry/backoff configured and what are the defaults? — and return the actual source lines in grep format
                  2. Understand semantic intent — e.g. find the error handling around the gitea API calls without needing to know the exact function names
                  3. Expose the RLM reasoning trace — rlmgrep -v shows iteration-by-iteration reasoning, which is audit-worthy for AI-assisted toolchains
                  Evaluation Criteria
                  •  Install rlmgrep: uv tool install --python 3.11 rlmgrep
                  •  Run against terraphim-ai Rust codebase — test semantic queries about error handling, executor selection, RLM hook invocation
                  •  Run against terraphim/terraphim-skills skill definitions — test natural-language skill discovery
                  •  Compare output quality vs grep -r and gtr for the same queries
                  •  Evaluate --answer mode for generating code answers grounded in actual source
                  •  Assess whether the verbose RLM trace (-v) is useful for agent audit trails
                  •  Document findings in .docs/rlmgrep-evaluation.md
                  rlmgrep Key Features to Test
                  FeatureWhat to test
                  --answerNatural-language code Q&A with citations
                  -C NContext lines in grep format
                  -v verboseFull RLM iteration traces
                  PDF/Office supportSkill docs in .docs/
                  Multi-providerOpenAI vs Anthropic vs Gemini outputs
                  Sidecar cachingImage/audio description caching
                  References
                  • rlmgrep repo: github.com/halfprice06/rlmgrep
                  • Author: @gooby_esq (Daniel Price)
                  • Install: uv tool install --python 3.11 rlmgrep
                  • RLM concept: DSPy RLM — LLM that generates code to fetch information, then reasons over results before submitting
                  Labels
                  feature/evaluation, AI/RLM, good-first-issue
                  Priority
                  P2 — informational/value assessment before committing any integration work.
                  Activity
                  Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
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                  No one assigned
                    Labels
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                    No labels
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                    Projects
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                      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
                      [feat] Evaluate rlmgrep for terraphim-ai codebase search #871
                      Open
                      Open
                      [feat] Evaluate rlmgrep for terraphim-ai codebase search#871
                      Description
                      @AlexMikhalev
                      AlexMikhalev
                      opened on May 16, 2026
                      Context
                      rlmgrep (github.com/halfprice06/rlmgrep) is a grep-shaped CLI search tool powered by DSPy's RLM (Refined Language Model). It accepts natural-language queries and returns matches in grep-like format, with full visibility into the RLM's reasoning loop (via rlmgrep -v).
                      Relevant signal: Alex has liked and bookmarked the rlmgrep launch tweet, indicating strong interest in RLM-based search for codebases.
                      Problem Statement
                      Current codebase search tools (grep, ripgrep, gtr for issue triage) operate on text/regex patterns. RLM-based search could:
                      1. Answer natural-language questions about the codebase — Where is retry/backoff configured and what are the defaults? — and return the actual source lines in grep format
                      2. Understand semantic intent — e.g. find the error handling around the gitea API calls without needing to know the exact function names
                      3. Expose the RLM reasoning trace — rlmgrep -v shows iteration-by-iteration reasoning, which is audit-worthy for AI-assisted toolchains
                      Evaluation Criteria
                      •  Install rlmgrep: uv tool install --python 3.11 rlmgrep
                      •  Run against terraphim-ai Rust codebase — test semantic queries about error handling, executor selection, RLM hook invocation
                      •  Run against terraphim/terraphim-skills skill definitions — test natural-language skill discovery
                      •  Compare output quality vs grep -r and gtr for the same queries
                      •  Evaluate --answer mode for generating code answers grounded in actual source
                      •  Assess whether the verbose RLM trace (-v) is useful for agent audit trails
                      •  Document findings in .docs/rlmgrep-evaluation.md
                      rlmgrep Key Features to Test
                      FeatureWhat to test
                      --answerNatural-language code Q&A with citations
                      -C NContext lines in grep format
                      -v verboseFull RLM iteration traces
                      PDF/Office supportSkill docs in .docs/
                      Multi-providerOpenAI vs Anthropic vs Gemini outputs
                      Sidecar cachingImage/audio description caching
                      References
                      • rlmgrep repo: github.com/halfprice06/rlmgrep
                      • Author: @gooby_esq (Daniel Price)
                      • Install: uv tool install --python 3.11 rlmgrep
                      • RLM concept: DSPy RLM — LLM that generates code to fetch information, then reasons over results before submitting
                      Labels
                      feature/evaluation, AI/RLM, good-first-issue
                      Priority
                      P2 — informational/value assessment before committing any integration work.
                      Activity
                      Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
                      Metadata
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                      Assignees
                      No one assigned
                        Labels
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                          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
                          [feat] Evaluate rlmgrep for terraphim-ai codebase search #871
                          Open
                          Open
                          [feat] Evaluate rlmgrep for terraphim-ai codebase search#871
                          Description
                          @AlexMikhalev
                          AlexMikhalev
                          opened on May 16, 2026
                          Context
                          rlmgrep (github.com/halfprice06/rlmgrep) is a grep-shaped CLI search tool powered by DSPy's RLM (Refined Language Model). It accepts natural-language queries and returns matches in grep-like format, with full visibility into the RLM's reasoning loop (via rlmgrep -v).
                          Relevant signal: Alex has liked and bookmarked the rlmgrep launch tweet, indicating strong interest in RLM-based search for codebases.
                          Problem Statement
                          Current codebase search tools (grep, ripgrep, gtr for issue triage) operate on text/regex patterns. RLM-based search could:
                          1. Answer natural-language questions about the codebase — Where is retry/backoff configured and what are the defaults? — and return the actual source lines in grep format
                          2. Understand semantic intent — e.g. find the error handling around the gitea API calls without needing to know the exact function names
                          3. Expose the RLM reasoning trace — rlmgrep -v shows iteration-by-iteration reasoning, which is audit-worthy for AI-assisted toolchains
                          Evaluation Criteria
                          •  Install rlmgrep: uv tool install --python 3.11 rlmgrep
                          •  Run against terraphim-ai Rust codebase — test semantic queries about error handling, executor selection, RLM hook invocation
                          •  Run against terraphim/terraphim-skills skill definitions — test natural-language skill discovery
                          •  Compare output quality vs grep -r and gtr for the same queries
                          •  Evaluate --answer mode for generating code answers grounded in actual source
                          •  Assess whether the verbose RLM trace (-v) is useful for agent audit trails
                          •  Document findings in .docs/rlmgrep-evaluation.md
                          rlmgrep Key Features to Test
                          FeatureWhat to test
                          --answerNatural-language code Q&A with citations
                          -C NContext lines in grep format
                          -v verboseFull RLM iteration traces
                          PDF/Office supportSkill docs in .docs/
                          Multi-providerOpenAI vs Anthropic vs Gemini outputs
                          Sidecar cachingImage/audio description caching
                          References
                          • rlmgrep repo: github.com/halfprice06/rlmgrep
                          • Author: @gooby_esq (Daniel Price)
                          • Install: uv tool install --python 3.11 rlmgrep
                          • RLM concept: DSPy RLM — LLM that generates code to fetch information, then reasons over results before submitting
                          Labels
                          feature/evaluation, AI/RLM, good-first-issue
                          Priority
                          P2 — informational/value assessment before committing any integration work.
                          Activity
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, '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); }
})();
})();

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                              [feat] Evaluate rlmgrep for terraphim-ai codebase search #871
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                              Open
                              [feat] Evaluate rlmgrep for terraphim-ai codebase search#871
                              Description
                              @AlexMikhalev
                              AlexMikhalev
                              opened on May 16, 2026
                              Context
                              rlmgrep (github.com/halfprice06/rlmgrep) is a grep-shaped CLI search tool powered by DSPy's RLM (Refined Language Model). It accepts natural-language queries and returns matches in grep-like format, with full visibility into the RLM's reasoning loop (via rlmgrep -v).
                              Relevant signal: Alex has liked and bookmarked the rlmgrep launch tweet, indicating strong interest in RLM-based search for codebases.
                              Problem Statement
                              Current codebase search tools (grep, ripgrep, gtr for issue triage) operate on text/regex patterns. RLM-based search could:
                              1. Answer natural-language questions about the codebase — Where is retry/backoff configured and what are the defaults? — and return the actual source lines in grep format
                              2. Understand semantic intent — e.g. find the error handling around the gitea API calls without needing to know the exact function names
                              3. Expose the RLM reasoning trace — rlmgrep -v shows iteration-by-iteration reasoning, which is audit-worthy for AI-assisted toolchains
                              Evaluation Criteria
                              •  Install rlmgrep: uv tool install --python 3.11 rlmgrep
                              •  Run against terraphim-ai Rust codebase — test semantic queries about error handling, executor selection, RLM hook invocation
                              •  Run against terraphim/terraphim-skills skill definitions — test natural-language skill discovery
                              •  Compare output quality vs grep -r and gtr for the same queries
                              •  Evaluate --answer mode for generating code answers grounded in actual source
                              •  Assess whether the verbose RLM trace (-v) is useful for agent audit trails
                              •  Document findings in .docs/rlmgrep-evaluation.md
                              rlmgrep Key Features to Test
                              FeatureWhat to test
                              --answerNatural-language code Q&A with citations
                              -C NContext lines in grep format
                              -v verboseFull RLM iteration traces
                              PDF/Office supportSkill docs in .docs/
                              Multi-providerOpenAI vs Anthropic vs Gemini outputs
                              Sidecar cachingImage/audio description caching
                              References
                              • rlmgrep repo: github.com/halfprice06/rlmgrep
                              • Author: @gooby_esq (Daniel Price)
                              • Install: uv tool install --python 3.11 rlmgrep
                              • RLM concept: DSPy RLM — LLM that generates code to fetch information, then reasons over results before submitting
                              Labels
                              feature/evaluation, AI/RLM, good-first-issue
                              Priority
                              P2 — informational/value assessment before committing any integration work.
                              Activity
                              Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
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                                Labels
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                                No labels
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                                  Milestone
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                                  Development
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                                  Issue actions