Phase 3: Success-rate monitoring and self-healing procedures #695

Closed
Closed
Phase 3: Success-rate monitoring and self-healing procedures#695
Labels
enhancementNew feature or request

Description

@AlexMikhalev
AlexMikhalev
opened on Mar 16, 2026

Parent Epic

Part of #692 (Operational Skill Store)

Summary

Track procedure confidence scores over time. When a procedure degrades (success rate drops below threshold), auto-pull it from replay and flag for re-learning. This is the "self-healing" layer that prevents agents from replaying broken workflows.

What Changes

Health tracking in terraphim_agent_evolution

CLI

terraphim-agent learn health # all procedures
terraphim-agent learn health --degraded-only # only degraded/broken
terraphim-agent learn health --task-type "deploy"

Auto-pull logic

When replay is requested for a Broken procedure:

  • Refuse replay, display health report
  • Suggest re-capture: "This procedure has failed 6 of last 10 times. Re-capture with: learn capture-success ..."

EIDOS integration

Each health state transition generates a prediction:

Affected Crates

  • terraphim_agent_evolution (health monitoring)
  • terraphim_agent (health CLI, auto-pull in replay)

Dependencies

Acceptance Criteria

  • Health report computed from rolling window of last N executions
  • Procedures auto-transition between health states
  • Broken procedures refused for replay with clear message
  • Health transitions emit EIDOS-compatible predictions
  • learn health CLI displays formatted report
  • Unit tests for health state transitions

Activity

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    enhancementNew feature or request

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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
      Phase 3: Success-rate monitoring and self-healing procedures #695
      Closed
      Closed
      Phase 3: Success-rate monitoring and self-healing procedures#695
      Labels
      enhancementNew feature or request
      Description
      @AlexMikhalev
      AlexMikhalev
      opened on Mar 16, 2026
      Parent Epic
      Part of #692 (Operational Skill Store)
      Summary
      Track procedure confidence scores over time. When a procedure degrades (success rate drops below threshold), auto-pull it from replay and flag for re-learning. This is the "self-healing" layer that prevents agents from replaying broken workflows.
      What Changes
      Health tracking in terraphim_agent_evolution
      CLI
      terraphim-agent learn health # all procedures
terraphim-agent learn health --degraded-only # only degraded/broken
terraphim-agent learn health --task-type "deploy"
      Auto-pull logic
      When replay is requested for a Broken procedure:
      • Refuse replay, display health report
      • Suggest re-capture: "This procedure has failed 6 of last 10 times. Re-capture with: learn capture-success ..."
      EIDOS integration
      Each health state transition generates a prediction:
      Affected Crates
      • terraphim_agent_evolution (health monitoring)
      • terraphim_agent (health CLI, auto-pull in replay)
      Dependencies
      Acceptance Criteria
      •  Health report computed from rolling window of last N executions
      •  Procedures auto-transition between health states
      •  Broken procedures refused for replay with clear message
      •  Health transitions emit EIDOS-compatible predictions
      • learn health CLI displays formatted report
      •  Unit tests for health state transitions
      Activity
      Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
      Metadata
      Metadata
      Assignees
      No one assigned
        Labels
        enhancementNew feature or request
        Type
        No type
        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
          Phase 3: Success-rate monitoring and self-healing procedures #695
          Closed
          Closed
          Phase 3: Success-rate monitoring and self-healing procedures#695
          Labels
          enhancementNew feature or request
          Description
          @AlexMikhalev
          AlexMikhalev
          opened on Mar 16, 2026
          Parent Epic
          Part of #692 (Operational Skill Store)
          Summary
          Track procedure confidence scores over time. When a procedure degrades (success rate drops below threshold), auto-pull it from replay and flag for re-learning. This is the "self-healing" layer that prevents agents from replaying broken workflows.
          What Changes
          Health tracking in terraphim_agent_evolution
          CLI
          terraphim-agent learn health # all procedures
terraphim-agent learn health --degraded-only # only degraded/broken
terraphim-agent learn health --task-type "deploy"
          Auto-pull logic
          When replay is requested for a Broken procedure:
          • Refuse replay, display health report
          • Suggest re-capture: "This procedure has failed 6 of last 10 times. Re-capture with: learn capture-success ..."
          EIDOS integration
          Each health state transition generates a prediction:
          Affected Crates
          • terraphim_agent_evolution (health monitoring)
          • terraphim_agent (health CLI, auto-pull in replay)
          Dependencies
          Acceptance Criteria
          •  Health report computed from rolling window of last N executions
          •  Procedures auto-transition between health states
          •  Broken procedures refused for replay with clear message
          •  Health transitions emit EIDOS-compatible predictions
          • learn health CLI displays formatted report
          •  Unit tests for health state transitions
          Activity
          Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
          Metadata
          Metadata
          Assignees
          No one assigned
            Labels
            enhancementNew feature or request
            Type
            No type
            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
              Phase 3: Success-rate monitoring and self-healing procedures #695
              Closed
              Closed
              Phase 3: Success-rate monitoring and self-healing procedures#695
              Labels
              enhancementNew feature or request
              Description
              @AlexMikhalev
              AlexMikhalev
              opened on Mar 16, 2026
              Parent Epic
              Part of #692 (Operational Skill Store)
              Summary
              Track procedure confidence scores over time. When a procedure degrades (success rate drops below threshold), auto-pull it from replay and flag for re-learning. This is the "self-healing" layer that prevents agents from replaying broken workflows.
              What Changes
              Health tracking in terraphim_agent_evolution
              CLI
              terraphim-agent learn health # all procedures
terraphim-agent learn health --degraded-only # only degraded/broken
terraphim-agent learn health --task-type "deploy"
              Auto-pull logic
              When replay is requested for a Broken procedure:
              • Refuse replay, display health report
              • Suggest re-capture: "This procedure has failed 6 of last 10 times. Re-capture with: learn capture-success ..."
              EIDOS integration
              Each health state transition generates a prediction:
              Affected Crates
              • terraphim_agent_evolution (health monitoring)
              • terraphim_agent (health CLI, auto-pull in replay)
              Dependencies
              Acceptance Criteria
              •  Health report computed from rolling window of last N executions
              •  Procedures auto-transition between health states
              •  Broken procedures refused for replay with clear message
              •  Health transitions emit EIDOS-compatible predictions
              • learn health CLI displays formatted report
              •  Unit tests for health state transitions
              Activity
              Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
              Metadata
              Metadata
              Assignees
              No one assigned
                Labels
                enhancementNew feature or request
                Type
                No type
                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
                  Phase 3: Success-rate monitoring and self-healing procedures #695
                  Closed
                  Closed
                  Phase 3: Success-rate monitoring and self-healing procedures#695
                  Labels
                  enhancementNew feature or request
                  Description
                  @AlexMikhalev
                  AlexMikhalev
                  opened on Mar 16, 2026
                  Parent Epic
                  Part of #692 (Operational Skill Store)
                  Summary
                  Track procedure confidence scores over time. When a procedure degrades (success rate drops below threshold), auto-pull it from replay and flag for re-learning. This is the "self-healing" layer that prevents agents from replaying broken workflows.
                  What Changes
                  Health tracking in terraphim_agent_evolution
                  CLI
                  terraphim-agent learn health # all procedures
terraphim-agent learn health --degraded-only # only degraded/broken
terraphim-agent learn health --task-type "deploy"
                  Auto-pull logic
                  When replay is requested for a Broken procedure:
                  • Refuse replay, display health report
                  • Suggest re-capture: "This procedure has failed 6 of last 10 times. Re-capture with: learn capture-success ..."
                  EIDOS integration
                  Each health state transition generates a prediction:
                  Affected Crates
                  • terraphim_agent_evolution (health monitoring)
                  • terraphim_agent (health CLI, auto-pull in replay)
                  Dependencies
                  Acceptance Criteria
                  •  Health report computed from rolling window of last N executions
                  •  Procedures auto-transition between health states
                  •  Broken procedures refused for replay with clear message
                  •  Health transitions emit EIDOS-compatible predictions
                  • learn health CLI displays formatted report
                  •  Unit tests for health state transitions
                  Activity
                  Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
                  Metadata
                  Metadata
                  Assignees
                  No one assigned
                    Labels
                    enhancementNew feature or request
                    Type
                    No type
                    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
                      Phase 3: Success-rate monitoring and self-healing procedures #695
                      Closed
                      Closed
                      Phase 3: Success-rate monitoring and self-healing procedures#695
                      Labels
                      enhancementNew feature or request
                      Description
                      @AlexMikhalev
                      AlexMikhalev
                      opened on Mar 16, 2026
                      Parent Epic
                      Part of #692 (Operational Skill Store)
                      Summary
                      Track procedure confidence scores over time. When a procedure degrades (success rate drops below threshold), auto-pull it from replay and flag for re-learning. This is the "self-healing" layer that prevents agents from replaying broken workflows.
                      What Changes
                      Health tracking in terraphim_agent_evolution
                      CLI
                      terraphim-agent learn health # all procedures
terraphim-agent learn health --degraded-only # only degraded/broken
terraphim-agent learn health --task-type "deploy"
                      Auto-pull logic
                      When replay is requested for a Broken procedure:
                      • Refuse replay, display health report
                      • Suggest re-capture: "This procedure has failed 6 of last 10 times. Re-capture with: learn capture-success ..."
                      EIDOS integration
                      Each health state transition generates a prediction:
                      Affected Crates
                      • terraphim_agent_evolution (health monitoring)
                      • terraphim_agent (health CLI, auto-pull in replay)
                      Dependencies
                      Acceptance Criteria
                      •  Health report computed from rolling window of last N executions
                      •  Procedures auto-transition between health states
                      •  Broken procedures refused for replay with clear message
                      •  Health transitions emit EIDOS-compatible predictions
                      • learn health CLI displays formatted report
                      •  Unit tests for health state transitions
                      Activity
                      Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
                      Metadata
                      Metadata
                      Assignees
                      No one assigned
                        Labels
                        enhancementNew feature or request
                        Type
                        No type
                        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
                          Phase 3: Success-rate monitoring and self-healing procedures #695
                          Closed
                          Closed
                          Phase 3: Success-rate monitoring and self-healing procedures#695
                          Labels
                          enhancementNew feature or request
                          Description
                          @AlexMikhalev
                          AlexMikhalev
                          opened on Mar 16, 2026
                          Parent Epic
                          Part of #692 (Operational Skill Store)
                          Summary
                          Track procedure confidence scores over time. When a procedure degrades (success rate drops below threshold), auto-pull it from replay and flag for re-learning. This is the "self-healing" layer that prevents agents from replaying broken workflows.
                          What Changes
                          Health tracking in terraphim_agent_evolution
                          CLI
                          terraphim-agent learn health # all procedures
terraphim-agent learn health --degraded-only # only degraded/broken
terraphim-agent learn health --task-type "deploy"
                          Auto-pull logic
                          When replay is requested for a Broken procedure:
                          • Refuse replay, display health report
                          • Suggest re-capture: "This procedure has failed 6 of last 10 times. Re-capture with: learn capture-success ..."
                          EIDOS integration
                          Each health state transition generates a prediction:
                          Affected Crates
                          • terraphim_agent_evolution (health monitoring)
                          • terraphim_agent (health CLI, auto-pull in replay)
                          Dependencies
                          Acceptance Criteria
                          •  Health report computed from rolling window of last N executions
                          •  Procedures auto-transition between health states
                          •  Broken procedures refused for replay with clear message
                          •  Health transitions emit EIDOS-compatible predictions
                          • learn health CLI displays formatted report
                          •  Unit tests for health state transitions
                          Activity
                          Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
                          Metadata
                          Metadata
                          Assignees
                          No one assigned
                            Labels
                            enhancementNew feature or request
                            Type
                            No type
                            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
                              Phase 3: Success-rate monitoring and self-healing procedures #695
                              Closed
                              Closed
                              Phase 3: Success-rate monitoring and self-healing procedures#695
                              Labels
                              enhancementNew feature or request
                              Description
                              @AlexMikhalev
                              AlexMikhalev
                              opened on Mar 16, 2026
                              Parent Epic
                              Part of #692 (Operational Skill Store)
                              Summary
                              Track procedure confidence scores over time. When a procedure degrades (success rate drops below threshold), auto-pull it from replay and flag for re-learning. This is the "self-healing" layer that prevents agents from replaying broken workflows.
                              What Changes
                              Health tracking in terraphim_agent_evolution
                              CLI
                              terraphim-agent learn health # all procedures
terraphim-agent learn health --degraded-only # only degraded/broken
terraphim-agent learn health --task-type "deploy"
                              Auto-pull logic
                              When replay is requested for a Broken procedure:
                              • Refuse replay, display health report
                              • Suggest re-capture: "This procedure has failed 6 of last 10 times. Re-capture with: learn capture-success ..."
                              EIDOS integration
                              Each health state transition generates a prediction:
                              Affected Crates
                              • terraphim_agent_evolution (health monitoring)
                              • terraphim_agent (health CLI, auto-pull in replay)
                              Dependencies
                              Acceptance Criteria
                              •  Health report computed from rolling window of last N executions
                              •  Procedures auto-transition between health states
                              •  Broken procedures refused for replay with clear message
                              •  Health transitions emit EIDOS-compatible predictions
                              • learn health CLI displays formatted report
                              •  Unit tests for health state transitions
                              Activity
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