[aw] Daily Ambient Context Optimizer failed #66272

{"type":"assistant.message","timestamp":"2026-10-06T19:52:47.679Z","id":"a5a5a5a5-2ad5-472a-b88d-7e3c45cc31cf","parentId":"aee11fbf-f656-4d91-9b4c-17a916ec676e","data":{"content":""}}
{"type":"tool.execution_start","timestamp":"2026-10-06T19:52:47.681Z","id":"c7c62bab-9f03-41c2-934d-53b037e0c5b3","parentId":"a5a5a5a5-2ad5-472a-b88d-7e3c45cc31cf","data":{"toolName":"bash","mcpServerName":"","toolCallId":"toolu_015kBa4fLj5ouFVaXN7UatVV","input":{"command":"cd /home/runner/work/gh-aw/gh-aw/.github/workflows; grep -n '^#\\|^imports\\|^  - ' issue-monster.md | head -60; grep -n '^#' deep-report.md | head -30; grep -n 'cli-proxy\\|toolsets' issue-monster.md deep-report.md"},"command":"cd /home/runner/work/gh-aw/gh-aw/.github/workflows; grep -n '^#\\|^imports\\|^  - ' issue-monster.md | head -60; grep -n '^#' deep-report.md | head -30; grep -n 'cli-proxy\\|toolsets' issue-monster.md deep-report.md"}}
{"type":"tool.execution_complete","timestamp":"2026-10-06T19:52:47.701Z","id":"07aaed46-08fa-4042-a998-d72bbd14348f","parentId":"d161a268-dd0b-47bc-a99e-348594e40ebe","data":{"toolName":"bash","mcpServerName":"","toolCallId":"toolu_015kBa4fLj5ouFVaXN7UatVV","success":true,"result":{"content":"515:imports:\n516:  - shared/mcp-pagination.md\n517:  - shared/github-guard-policy.md\n518:  - shared/activation-app.md\n520:  - shared/otlp.md\n557:  - id: issue_assigned\n559:  - id: single_issue_scoped\n565:# Issue Monster 🍪\n569:## Your Mission\n573:## Current Context\n579:## Step-by-Step Process\n581:### 1. Review Pre-Searched and Prioritized Issue List\n635:### 1a. Handle Parent-Child Issue Relationships (for \"task\" or \"plan\" labeled issues)\n654:### 2. Select Up to Three Issues to Work On\n660:  - Different areas of the codebase (e.g., one CLI issue, one workflow issue, one docs issue)\n661:  - Different features or components\n662:  - No overlapping file changes expected\n663:  - Different problem domains\n665:  - Start from the top of the sorted list (highest scores)\n666:  - Skip issues that would conflict with already-selected issues\n667:  - For \"task\" sub-issues: Process in order (oldest first among siblings)\n668:  - Clearly independent from each other\n688:### 3. Validate Selected Issues (Body-First)\n699:#### Handling Integrity-Blocked Issues\n715:### 4. Assign Issues to Copilot Agent\n735:### 4a. Handle Retry-Blocked Issues\n747:### 5. Add Comment to Each Assigned Issue\n757:## skill: `issue-monster-token-budget`\n773:## skill: `issue-monster-report-formatting`\n782:### Recommended Report Structure\n789:## Success Criteria\n798:## Error Handling\n105:### DeepReport - Intelligence Gathering Agent\n114:#### Mission\n125:#### Data Sources\n127:### Primary: GitHub Discussions\n137:### Secondary: Workflow Logs\n145:### Tertiary: Repository Issues\n157:#### Intelligence Collection Process\n159:### Step 0: Check Repo Memory\n172:### Step 1: Gather Discussion Intelligence\n188:### Step 2: Gather Workflow Intelligence\n208:### Step 2.5: Analyze Repository Issues\n212:### Step 2.7: Mine Discussions for Code Quality Tasks\n230:### Step 3: Cross-Reference and Analyze\n244:### Step 4: Store Insights in Repo Memory\n254:#### Actionable Task Creation\n292:#### Report Structure\n318:### 🔍 Executive Summary\n325:### 📊 Pattern Analysis\n338:### 📈 Trend Intelligence\n348:### 🚨 Notable Findings\n355:### 🔮 Predictions and Recommendations\n363:### ✅ Actionable Agentic Tasks (Quick Wins)\n367:### 📚 Source Attribution\n376:#### Final Steps\n380:#### agent: `issues-analyst`\nissue-monster.md:524:  cli-proxy: true\nissue-monster.md:528:    toolsets: [issues]\ndeep-report.md:79:  cli-proxy: true\ndeep-report.md:84:      toolsets: [default, actions, discussions, search]\n<shellId: 8 completed with exit code 0>","detailedContent":"515:imports:\n516:  - shared/mcp-pagination.md\n517:  - shared/github-guard-policy.md\n518:  - shared/activation-app.md\n520:  - shared/otlp.md\n557:  - id: issue_assigned\n559:  - id: single_issue_scoped\n565:# Issue Monster 🍪\n569:## Your Mission\n573:## Current Context\n579:## Step-by-Step Process\n581:### 1. Review Pre-Searched and Prioritized Issue List\n635:### 1a. Handle Parent-Child Issue Relationships (for \"task\" or \"plan\" labeled issues)\n654:### 2. Select Up to Three Issues to Work On\n660:  - Different areas of the codebase (e.g., one CLI issue, one workflow issue, one docs issue)\n661:  - Different features or components\n662:  - No overlapping file changes expected\n663:  - Different problem domains\n665:  - Start from the top of the sorted list (highest scores)\n666:  - Skip issues that would conflict with already-selected issues\n667:  - For \"task\" sub-issues: Process in order (oldest first among siblings)\n668:  - Clearly independent from each other\n688:### 3. Validate Selected Issues (Body-First)\n699:#### Handling Integrity-Blocked Issues\n715:### 4. Assign Issues to Copilot Agent\n735:### 4a. Handle Retry-Blocked Issues\n747:### 5. Add Comment to Each Assigned Issue\n757:## skill: `issue-monster-token-budget`\n773:## skill: `issue-monster-report-formatting`\n782:### Recommended Report Structure\n789:## Success Criteria\n798:## Error Handling\n105:### DeepReport - Intelligence Gathering Agent\n114:#### Mission\n125:#### Data Sources\n127:### Primary: GitHub Discussions\n137:### Secondary: Workflow Logs\n145:### Tertiary: Repository Issues\n157:#### Intelligence Collection Process\n159:### Step 0: Check Repo Memory\n172:### Step 1: Gather Discussion Intelligence\n188:### Step 2: Gather Workflow Intelligence\n208:### Step 2.5: Analyze Repository Issues\n212:### Step 2.7: Mine Discussions for Code Quality Tasks\n230:### Step 3: Cross-Reference and Analyze\n244:### Step 4: Store Insights in Repo Memory\n254:#### Actionable Task Creation\n292:#### Report Structure\n318:### 🔍 Executive Summary\n325:### 📊 Pattern Analysis\n338:### 📈 Trend Intelligence\n348:### 🚨 Notable Findings\n355:### 🔮 Predictions and Recommendations\n363:### ✅ Actionable Agentic Tasks (Quick Wins)\n367:### 📚 Source Attribution\n376:#### Final Steps\n380:#### agent: `issues-analyst`\nissue-monster.md:524:  cli-proxy: true\nissue-monster.md:528:    toolsets: [issues]\ndeep-report.md:79:  cli-proxy: true\ndeep-report.md:84:      toolsets: [default, actions, discussions, search]\n<shellId: 8 completed with exit code 0>","contents":[{"type":"shell_exit","shellId":"8","exitCode":0,"cwd":"/home/runner/work/gh-aw/gh-aw","outputPreview":"515:imports:\n516:  - shared/mcp-pagination.md\n517:  - shared/github-guard-policy.md\n518:  - shared/activation-app.md\n520:  - shared/otlp.md\n557:  - id: issue_assigned\n559:  - id: single_issue_scoped\n565:# Issue Monster 🍪\n569:## Your Mission\n573:## Current Context\n579:## Step-by-Step Process\n581:### 1. Review Pre-Searched and Prioritized Issue List\n635:### 1a. Handle Parent-Child Issue Relationships (for \"task\" or \"plan\" labeled issues)\n654:### 2. Select Up to Three Issues to Work On\n660:  - Different areas of the codebase (e.g., one CLI issue, one workflow issue, one docs issue)\n661:  - Different features or components\n662:  - No overlapping file changes expected\n663:  - Different problem domains\n665:  - Start from the top of the sorted list (highest scores)\n666:  - Skip issues that would conflict with already-selected issues\n667:  - For \"task\" sub-issues: Process in order (oldest first among siblings)\n668:  - Clearly independent from each other\n688:### 3. Validate Selected Issues (Body-First)\n699:#### Handling Integrity-Blocked Issues\n715:### 4. Assign Issues to Copilot Agent\n735:### 4a. Handle Retry-Blocked Issues\n747:### 5. Add Comment to Each Assigned Issue\n757:## skill: `issue-monster-token-budget`\n773:## skill: `issue-monster-report-formatting`\n782:### Recommended Report Structure\n789:## Success Criteria\n798:## Error Handling\n105:### DeepReport - Intelligence Gathering Agent\n114:#### Mission\n125:#### Data Sources\n127:### Primary: GitHub Discussions\n137:### Secondary: Workflow Logs\n145:### Tertiary: Repository Issues\n157:#### Intelligence Collection Process\n159:### Step 0: Check Repo Memory\n172:### Step 1: Gather Discussion Intelligence\n188:### Step 2: Gather Workflow Intelligence\n208:### Step 2.5: Analyze Repository Issues\n212:### Step 2.7: Mine Discussions for Code Quality Tasks\n230:### Step 3: Cross-Reference and Analyze\n244:### Step 4: Store Insights in Repo Memory\n254:#### Actionable Task Creation\n292:#### Report Structure\n318:### 🔍 Executive Summary\n325:### 📊 Pattern Analysis\n338:### 📈 Trend Intelligence\n348:### 🚨 Notable Findings\n355:### 🔮 Predictions and Recommendations\n363:### ✅ Actionable Agentic Tasks (Quick Wins)\n367:### 📚 Source Attribution\n376:#### Final Steps\n380:#### agent: `issues-analyst`\nissue-monster.md:524:  cli-proxy: true\nissue-monster.md:528:    toolsets: [issues]\ndeep-report.md:79:  cli-proxy: true\ndeep-report.md:84:      toolsets: [default, actions, discussions, search]\n"}]}}}
{"type":"assistant.message","timestamp":"2026-10-06T19:53:04.056Z","id":"c2ef55fc-76f8-4ccb-96d6-3b4342695d38","parentId":"ede23c5b-d196-4b76-93e8-44f3c5530c75","data":{"content":""}}
{"type":"tool.execution_start","timestamp":"2026-10-06T19:53:04.059Z","id":"c0d851b2-2915-4751-aa6c-bf17278dd901","parentId":"c2ef55fc-76f8-4ccb-96d6-3b4342695d38","data":{"toolName":"bash","mcpServerName":"","toolCallId":"toolu_01VuMaKoadLm5RLRnnMeWSLd","input":{"command":"cat > /tmp/gh-aw/ambient-context/body.md <<'EOF'\n### Executive Summary\n- Runs listed: 60 (partial, 17:43–19:45 UTC); audited 1 (`37508923389`). **Reduced-data report**: the run artifact directory `/tmp/gh-aw/aw-mcp/logs` was permission-denied in this sandbox, so no first-request text (`event-logs.jsonl`) could be extracted and the deterministic Python analysis was **not** run. No char/token metrics are claimed.\n- Evidence used: run metadata (aic/tokens), one audit, and current workflow source sizes.\n- Conclusion: the largest controllable ambient context is in large workflow markdown bodies (`issue-monster.md` 41.5 KB, `deep-report.md` 18.8 KB) with inline step/report templates.\n\n### Highest-Leverage Changes\n1. `issue-monster.md` (workflow-md, impact medium, manual review): ~41.5 KB; its prompt body spans ~230 lines of step-by-step process (lines 565–800) after ~500 lines of frontmatter/pre-steps. Move deterministic issue scoring/filtering fully into `steps:` and keep only decision rules in the prompt; the existing `## skill:` blocks (token-budget, report-formatting) show the pattern. Run had aic 32.5 and 632,912 tokens. Keep any reduction ≤40%.\n2. `deep-report.md` (workflow-md + agents, impact medium, manual review): 18.8 KB, highest aic in sample (421.8, 46,368 tokens, failed). Report structure template (lines ~292–375, 8 headed sections) is inline; move it into a `## skill:` block loaded on demand. Re-evaluate whether the inline `agent: issues-analyst` (line 380) justifies being in every first request.\n3. `impeccable-skills-reviewer.md` (skills, impact low): aic 175 / 74,490 tokens in a 1-turn run despite a 6 KB source — suggests skill/ambient content outside the workflow body dominates; capture first-request text next run to confirm before editing. Safe to investigate only.\n4. Tooling readiness: `issue-monster` has `cli-proxy: true` but only `toolsets: [issues]`; confirm needed toolsets and replace any raw `gh aw` shell wording with `agentic-workflows` MCP tool calls. Safe immediately after review.\n5. Not recommended (blocked by closed PR #65568 in last 14 days): `mattpocock-skills-reviewer.md`, `pr-code-quality-reviewer.md` (both high-cost in sample: aic 133 and 46, tokens up to 715K).\n\n### CI-Validation Checklist for Implementing Agents\n\n- [ ] Run `make recompile` for every modified `.github/workflows/*.md` file — zero compilation errors required\n- [ ] Confirm no target workflow file is reduced by more than 40% of its current character count\n- [ ] Run `make agent-report-progress` before the final commit and confirm it passes\n- [ ] Check the `blocked_files` list in `/tmp/gh-aw/ambient-context/closed-pr-targets.json` — **do not re-attempt changes to any file that appears in a closed ambient-context optimization PR from the last 14 days**\n- [ ] Include a smoke-test result or dry-run output in the PR description for every changed workflow spec\n- [ ] Document all generated `.lock.yml` changes in the PR body\n- [ ] Do not submit as a draft PR\n\n### Key Metrics\n| Metric | Value |\n|---|---|\n| Sampled runs | 0 with first-request text (60 listed, 1 audited) |\n| Distinct workflows | n/a |\n| Median chars | n/a (artifacts inaccessible) |\n| P95 chars | n/a |\n| Largest sampled request | n/a |\n| Merged optimizer PRs (7d) | 0 |\n| Closed optimizer PRs (7d) | 1 |\n| Optimizer PR close-rate (7d) | null (<3 settled PRs; auto_pause false) |\n| WSRF (audited runs) | 1.02 (run 37508923389; peak 5,418 vs cumulative 5,546 input tokens, 65 invocations) |\n\n<details>\n<summary><b>Per-Run First-Request Metrics</b></summary>\n\n| Run | Workflow | aic | tokens | turns |\n|---|---|---|---|---|\n| 37511664816 | Deep Report (failure) | 421.8 | 46,368 | n/a |\n| 37508923389 | Impeccable Skills Reviewer | 175.0 | 74,490 | 1 |\n| 37508897038 | Matt Pocock Skills Reviewer | 132.8 | 41,971 | 2 |\n| 37508923161 | PR Code Quality Reviewer | 46.0 | 715,214 | 2 |\n\nRequest char/line metrics unavailable.\n</details>\n\n<details>\n<summary><b>Repeated Ambient Context Signals / Deterministic Output</b></summary>\n\nNot computed: first-request artifacts were not readable. WSRF of 1.02 for the audited run indicates context is not being rebuilt across turns, so per-turn resend is not the problem there; first-request size is.\n</details>\n\n### Recommendations by Category\n#### Workflow Markdown\nItems 1, 2, 4 above.\n#### Skills\nItem 3 above.\n#### Agents\nItem 2 (inline `issues-analyst` agent in `deep-report.md`).\n\n### References\n- [§37511664816](https://github.com/github/gh-aw/actions/runs/37511664816)\n- [§37508923389](https://github.com/github/gh-aw/actions/runs/37508923389)\n- [§37508897038](https://github.com/github/gh-aw/actions/runs/37508897038)\nEOF\nwc -c /tmp/gh-aw/ambient-context/body.md\njq -Rs '{title:\"[ambient-context] Daily Ambient Context Optimizer - 2026-10-06\", body: .}' /tmp/gh-aw/ambient-context/body.md | safeoutputs create_issue ."},"command":"cat > /tmp/gh-aw/ambient-context/body.md <<'EOF'\n### Executive Summary\n- Runs listed: 60 (partial, 17:43–19:45 UTC); audited 1 (`37508923389`). **Reduced-data report**: the run artifact directory `/tmp/gh-aw/aw-mcp/logs` was permission-denied in this sandbox, so no first-request text (`event-logs.jsonl`) could be extracted and the deterministic Python analysis was **not** run. No char/token metrics are claimed.\n- Evidence used: run metadata (aic/tokens), one audit, and current workflow source sizes.\n- Conclusion: the largest controllable ambient context is in large workflow markdown bodies (`issue-monster.md` 41.5 KB, `deep-report.md` 18.8 KB) with inline step/report templates.\n\n### Highest-Leverage Changes\n1. `issue-monster.md` (workflow-md, impact medium, manual review): ~41.5 KB; its prompt body spans ~230 lines of step-by-step process (lines 565–800) after ~500 lines of frontmatter/pre-steps. Move deterministic issue scoring/filtering fully into `steps:` and keep only decision rules in the prompt; the existing `## skill:` blocks (token-budget, report-formatting) show the pattern. Run had aic 32.5 and 632,912 tokens. Keep any reduction ≤40%.\n2. `deep-report.md` (workflow-md + agents, impact medium, manual review): 18.8 KB, highest aic in sample (421.8, 46,368 tokens, failed). Report structure template (lines ~292–375, 8 headed sections) is inline; move it into a `## skill:` block loaded on demand. Re-evaluate whether the inline `agent: issues-analyst` (line 380) justifies being in every first request.\n3. `impeccable-skills-reviewer.md` (skills, impact low): aic 175 / 74,490 tokens in a 1-turn run despite a 6 KB source — suggests skill/ambient content outside the workflow body dominates; capture first-request text next run to confirm before editing. Safe to investigate only.\n4. Tooling readiness: `issue-monster` has `cli-proxy: true` but only `toolsets: [issues]`; confirm needed toolsets and replace any raw `gh aw` shell wording with `agentic-workflows` MCP tool calls. Safe immediately after review.\n5. Not recommended (blocked by closed PR #65568 in last 14 days): `mattpocock-skills-reviewer.md`, `pr-code-quality-reviewer.md` (both high-cost in sample: aic 133 and 46, tokens up to 715K).\n\n### CI-Validation Checklist for Implementing Agents\n\n- [ ] Run `make recompile` for every modified `.github/workflows/*.md` file — zero compilation errors required\n- [ ] Confirm no target workflow file is reduced by more than 40% of its current character count\n- [ ] Run `make agent-report-progress` before the final commit and confirm it passes\n- [ ] Check the `blocked_files` list in `/tmp/gh-aw/ambient-context/closed-pr-targets.json` — **do not re-attempt changes to any file that appears in a closed ambient-context optimization PR from the last 14 days**\n- [ ] Include a smoke-test result or dry-run output in the PR description for every changed workflow spec\n- [ ] Document all generated `.lock.yml` changes in the PR body\n- [ ] Do not submit as a draft PR\n\n### Key Metrics\n| Metric | Value |\n|---|---|\n| Sampled runs | 0 with first-request text (60 listed, 1 audited) |\n| Distinct workflows | n/a |\n| Median chars | n/a (artifacts inaccessible) |\n| P95 chars | n/a |\n| Largest sampled request | n/a |\n| Merged optimizer PRs (7d) | 0 |\n| Closed optimizer PRs (7d) | 1 |\n| Optimizer PR close-rate (7d) | null (<3 settled PRs; auto_pause false) |\n| WSRF (audited runs) | 1.02 (run 37508923389; peak 5,418 vs cumulative 5,546 input tokens, 65 invocations) |\n\n<details>\n<summary><b>Per-Run First-Request Metrics</b></summary>\n\n| Run | Workflow | aic | tokens | turns |\n|---|---|---|---|---|\n| 37511664816 | Deep Report (failure) | 421.8 | 46,368 | n/a |\n| 37508923389 | Impeccable Skills Reviewer | 175.0 | 74,490 | 1 |\n| 37508897038 | Matt Pocock Skills Reviewer | 132.8 | 41,971 | 2 |\n| 37508923161 | PR Code Quality Reviewer | 46.0 | 715,214 | 2 |\n\nRequest char/line metrics unavailable.\n</details>\n\n<details>\n<summary><b>Repeated Ambient Context Signals / Deterministic Output</b></summary>\n\nNot computed: first-request artifacts were not readable. WSRF of 1.02 for the audited run indicates context is not being rebuilt across turns, so per-turn resend is not the problem there; first-request size is.\n</details>\n\n### Recommendations by Category\n#### Workflow Markdown\nItems 1, 2, 4 above.\n#### Skills\nItem 3 above.\n#### Agents\nItem 2 (inline `issues-analyst` agent in `deep-report.md`).\n\n### References\n- [§37511664816](https://github.com/github/gh-aw/actions/runs/37511664816)\n- [§37508923389](https://github.com/github/gh-aw/actions/runs/37508923389)\n- [§37508897038](https://github.com/github/gh-aw/actions/runs/37508897038)\nEOF\nwc -c /tmp/gh-aw/ambient-context/body.md\njq -Rs '{title:\"[ambient-context] Daily Ambient Context Optimizer - 2026-10-06\", body: .}' /tmp/gh-aw/ambient-context/body.md | safeoutputs create_issue ."}}
{"type":"tool.execution_complete","timestamp":"2026-10-06T19:53:04.352Z","id":"72bb2717-7084-4ac3-a334-6f92dfbb2c0a","parentId":"a24a74b0-6ed7-4a7b-b152-688114498fd3","data":{"toolName":"bash","mcpServerName":"","toolCallId":"toolu_01VuMaKoadLm5RLRnnMeWSLd","success":true,"result":{"content":"4636 /tmp/gh-aw/ambient-context/body.md\n[info] [safeoutputs] Bridge invoked: argumentCount=1\n[info] [safeoutputs] Stdin captured: 4796 bytes\n[info] [safeoutputs] Calling tool 'create_issue' (4786 argument bytes)\n[info] [safeoutputs] MCP initialize: POST http://awmg-mcpg:8080/mcp/safeoutputs\n[info] [safeoutputs] MCP initialize: status=200, sessionId=3Y6ZD7Y4..., elapsed=18ms\n[info] [safeoutputs] MCP notifications/initialized\n[info] [safeoutputs] MCP notifications/initialized: done (6ms)\n[info] [safeoutputs] MCP keepalive started (interval=10000ms)\n[info] [safeoutputs] MCP tools/call: tool=create_issue, argumentBytes=4786\n[info] [safeoutputs] MCP tools/call: status=200, elapsed=214ms\n[info] [safeoutputs] MCP keepalive stopped\n[info] [safeoutputs] Tool call complete: total=240ms\n{\"result\":\"success\"}\n[info] [safeoutputs] Tool output: 20 chars\n<shellId: 9 completed with exit code 0>","detailedContent":"4636 /tmp/gh-aw/ambient-context/body.md\n[info] [safeoutputs] Bridge invoked: argumentCount=1\n[info] [safeoutputs] Stdin captured: 4796 bytes\n[info] [safeoutputs] Calling tool 'create_issue' (4786 argument bytes)\n[info] [safeoutputs] MCP initialize: POST http://awmg-mcpg:8080/mcp/safeoutputs\n[info] [safeoutputs] MCP initialize: status=200, sessionId=3Y6ZD7Y4..., elapsed=18ms\n[info] [safeoutputs] MCP notifications/initialized\n[info] [safeoutputs] MCP notifications/initialized: done (6ms)\n[info] [safeoutputs] MCP keepalive started (interval=10000ms)\n[info] [safeoutputs] MCP tools/call: tool=create_issue, argumentBytes=4786\n[info] [safeoutputs] MCP tools/call: status=200, elapsed=214ms\n[info] [safeoutputs] MCP keepalive stopped\n[info] [safeoutputs] Tool call complete: total=240ms\n{\"result\":\"success\"}\n[info] [safeoutputs] Tool output: 20 chars\n<shellId: 9 completed with exit code 0>","contents":[{"type":"shell_exit","shellId":"9","exitCode":0,"cwd":"/home/runner/work/gh-aw/gh-aw","outputPreview":"4636 /tmp/gh-aw/ambient-context/body.md\n[info] [safeoutputs] Bridge invoked: argumentCount=1\n[info] [safeoutputs] Stdin captured: 4796 bytes\n[info] [safeoutputs] Calling tool 'create_issue' (4786 argument bytes)\n[info] [safeoutputs] MCP initialize: POST http://awmg-mcpg:8080/mcp/safeoutputs\n[info] [safeoutputs] MCP initialize: status=200, sessionId=3Y6ZD7Y4..., elapsed=18ms\n[info] [safeoutputs] MCP notifications/initialized\n[info] [safeoutputs] MCP notifications/initialized: done (6ms)\n[info] [safeoutputs] MCP keepalive started (interval=10000ms)\n[info] [safeoutputs] MCP tools/call: tool=create_issue, argumentBytes=4786\n[info] [safeoutputs] MCP tools/call: status=200, elapsed=214ms\n[info] [safeoutputs] MCP keepalive stopped\n[info] [safeoutputs] Tool call complete: total=240ms\n{\"result\":\"success\"}\n[info] [safeoutputs] Tool output: 20 chars\n"}]}}}
[safeoutputs-cli] hasTerminalSafeOutput: terminal entry found in /home/runner/work/_temp/gh-aw/safeoutputs/outputs.jsonl: type=create_issue
{"type":"assistant.message","timestamp":"2026-10-06T19:53:08.614Z","id":"92d19246-fa45-4dd7-aa27-53fb6c2facc7","parentId":"83dec67f-fd4f-4f1f-b3cd-eddaef25e756","data":{"content":"I filed the issue, but it is a reduced-data report. The run artifact directory `/tmp/gh-aw/aw-mcp/logs` was permission-denied, so I couldn't extract any first-request text. I didn't run the Python analysis, and the issue has no character or token metrics.\n\nWhat the issue is based on:\n- **Run metadata:** the `logs` call listed 60 runs but returned a partial window of about two hours (17:43–19:45 UTC).\n- **Audit:** I audited one run, 37508923389. Its working-set rebuild factor is 1.02, so context isn't being rebuilt each turn there.\n- **Workflow sources:** I read the current sizes of `issue-monster.md` (41.5 KB) and `deep-report.md` (18.8 KB).\n\nThe issue recommends moving inline step and report templates in those two workflows into `## skill:` blocks or deterministic `steps:`. It also suggests checking the inline `issues-analyst` agent in `deep-report.md`, and confirming first-request size on the Impeccable Skills Reviewer before editing it.\n\nThe Matt Pocock and PR Code Quality reviewer workflows are excluded because they are blocked by closed PR #65568. The close-rate pre-step reported `auto_pause: false`, so the cap didn't apply."}}
[copilot-sdk-driver] [sdk-driver] session completed: hasOutput=true assistantTurns=1 durationMs=129046
{"type":"result","num_turns":12,"usage":{"input_tokens":402248,"output_tokens":4733,"cache_read_input_tokens":352658,"cache_creation_input_tokens":39441}}