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Analysis Period: Last 30 days (2026-06-16 → 2026-07-06) Total Copilot PRs Analyzed: 999 (of 1000 fetched; 1 body too short to cluster) Clusters Identified: 8 (K-means, k selected over 3–8) Overall Success Rate: 80.0% merged (799 merged · 194 closed · 6 open)
Clustering was performed on the PR bodies of app/copilot-swe-agent PRs in github/gh-aw, TF‐IDF vectorized (uni+bigrams, min_df=3) and grouped with K‐means. Themes below are labeled from top TF‐IDF terms and representative PRs.
Key Findings
Two themes dominate ~44% of all agent work: Engine/schema config & docs (230, 23%) and CI jobs, steps & safe-outputs (213, 21%). These are the workhorse categories.
Documentation/config-heavy work has the lowest merge rate. The two lowest-success clusters — Engine/schema & docs (73.0%) and Workflow authoring & prompts (75.8%) — are the ones dominated by docs/prompt/guidance churn, where "correct" is subjective and PRs are more often superseded or closed.
Mechanical, well-scoped work merges best.Firewall/network & version bumps (97.6%) and Go linter/helper refactors (85.4%) top the chart — narrow, testable changes with clear acceptance criteria.
Data caveat surfaced by clustering itself: cluster C0 ("sous-chef/aic/generated pr") is defined by boilerplate footer text leaking from PR bodies rather than task semantics. Roughly 9% of PRs carry this template, which fragments an otherwise-semantic clustering.
Full Analysis Report
General Insights
Most common task type: Engine/schema config & docs (23.0% of tasks)
Highest success rate: Firewall/network & version bumps — 97.6%
Top terms: engine, schema, added, updated, docs, copilot, runtime, new
Engine/runtime config, generated-schema updates, and Quick-Start/docs edits. Largest and lowest-success cluster — docs/config PRs are frequently reworked or closed.
Examples: #43743, #43715, #43697, #43766
Top terms: aic, sous, sous chef, chef, pr sous, generated pr, pr, generated
Cluster formed by shared boilerplate footer, not a single semantic theme (see caveat). Underlying changes are varied small fixes.
Examples: #43729, #43724, #43732, #43725
Top terms: actions, job, fix, plan make, make progress
Auto-remediation of failing GitHub Actions jobs; all [WIP] Fix failing ....
Examples: #43733, #43306, #43305, #43304
q: enforce small model for contribution-checker subagent
Model & sub-agent
MERGED
Recommendations
Tighten acceptance criteria for docs/config prompts (C2, C1). These two clusters (~39% of volume) sit ~5–7 pts below the mean merge rate. Prompts here should name the exact file/section, the desired end state, and a done-condition, to cut the rework-and-close churn.
Strip boilerplate footers before clustering / before agent context. The "sous-chef/aic/generated pr" template dominates C0 and pollutes term space. Filtering it would sharpen clustering and reduce token noise in agent prompts.
Lean into the high-success pattern for autonomy. Narrow, verifiable tasks (version bumps, firewall/domain edits, lint-rule refactors) merge at 85–98%. These are the safest candidates to expand agent coverage on.
Instrument turn-count/cost. Per-PR turn and cost metrics were unavailable this run (see limitations); wiring them in would let us correlate task type with effort, not just outcome.
Limitations
Workflow metrics (turns, duration, cost) not available. The pre-fetched pr-full-data cache (PRs 30577–34390) does not overlap the current 30-day window (PRs 39651–43766) — it is stale from a prior period — and these are copilot-swe-agent PRs, not gh-aw engine runs, so aw_info.json turn counts don't apply. Analysis uses PR bodies + outcomes only.
"Prompt" == PR body. No START COPILOT markers were present; the agent's PR description is used as the task proxy.
Silhouette scores are low (~0.03). Expected for sparse TF‐IDF text; clusters are semantically coherent by inspection but boundaries are soft. Treat cluster sizes as approximate.
Generated by Copilot Agent Prompt Clustering Analysis — Run §28787472646
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Summary
Analysis Period: Last 30 days (2026-06-16 → 2026-07-06)
Total Copilot PRs Analyzed: 999 (of 1000 fetched; 1 body too short to cluster)
Clusters Identified: 8 (K-means, k selected over 3–8)
Overall Success Rate: 80.0% merged (799 merged · 194 closed · 6 open)
Clustering was performed on the PR bodies of
app/copilot-swe-agentPRs ingithub/gh-aw, TF‐IDF vectorized (uni+bigrams, min_df=3) and grouped with K‐means. Themes below are labeled from top TF‐IDF terms and representative PRs.Key Findings
Full Analysis Report
General Insights
[WIP] Fix failing GitHub Actions job ..., a recurring auto-remediation pattern.Cluster Analysis
C2 · Engine/schema config & docs — 230 tasks (23.0%), 73.0% merged
Top terms:
engine, schema, added, updated, docs, copilot, runtime, newEngine/runtime config, generated-schema updates, and Quick-Start/docs edits. Largest and lowest-success cluster — docs/config PRs are frequently reworked or closed.
Examples: #43743, #43715, #43697, #43766
C5 · CI jobs, steps & safe-outputs — 213 tasks (21.3%), 79.8% merged
Top terms:
step, file, job, output, agent, changes, failure, safeWorkflow job wiring, CI drift checks, safe-output plumbing, PR-reviewer tooling.
Examples: #43747, #43730, #43658, #43716
C7 · Go linters/helpers & pkg refactors — 164 tasks (16.4%), 85.4% merged
Top terms:
helper, package, function, path, changes, flagged, added, casesESLint-factory rules, AST helper consolidation, false-positive exemptions. Well-scoped, test-backed → high merge rate.
Examples: #43649, #43692, #43731, #43748
C1 · Workflow authoring & prompts — 161 tasks (16.1%), 75.8% merged
Top terms:
workflow, workflows, prompt, guidance, issue, added, report, commandPrompt constraints, guidance docs, report/command tuning. Subjective acceptance → below-average merge rate.
Examples: #43744, #43699, #43681, #43659
C0 · Bot-generated fixes (sous-chef/aic) — 87 tasks (8.7%), 85.1% merged
Top terms:
aic, sous, sous chef, chef, pr sous, generated pr, pr, generatedCluster formed by shared boilerplate footer, not a single semantic theme (see caveat). Underlying changes are varied small fixes.
Examples: #43729, #43724, #43732, #43725
C3 · Engine model & sub-agent tuning — 86 tasks (8.6%), 83.7% merged
Top terms:
model, workflow, agent, tool, sub, sub agent, copilot, outputModel selection, sub-agent dispatch limits, tool-permission tuning.
Examples: #43672, #43673, #43679, #43621
C6 · Firewall/network & version bumps — 41 tasks (4.1%), 97.6% merged
Top terms:
domains, firewall, blocked, aic, workflow, smoke claude, claude, smokeFirewall domain lists, dependency/CLI version bumps, DNS fixes. Narrow + verifiable → highest success.
Examples: #43664, #43358, #43172, #43056
C4 · WIP CI-failure fixes — 17 tasks (1.7%), 76.5% merged
Top terms:
actions, job, fix, plan make, make progressAuto-remediation of failing GitHub Actions jobs; all
[WIP] Fix failing ....Examples: #43733, #43306, #43305, #43304
Success Rate by Cluster
Data Table (25 most recent PRs)
list_code_scanning_alertsprompt usageneeds.activation.outputs.*--trigger-contextissue URLssmallmodel for contribution-checker subagentRecommendations
Limitations
pr-full-datacache (PRs 30577–34390) does not overlap the current 30-day window (PRs 39651–43766) — it is stale from a prior period — and these arecopilot-swe-agentPRs, notgh-awengine runs, soaw_info.jsonturn counts don't apply. Analysis uses PR bodies + outcomes only.START COPILOTmarkers were present; the agent's PR description is used as the task proxy.Generated by Copilot Agent Prompt Clustering Analysis — Run §28787472646
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