Evaluate the build trail of a PR — read the claude -p sessions the harness ran to build it, find where the project's context (Expert / AGENTS.md / skill / spec) served or failed the agents, then capture the learnings as evals (regression tests over the harness's own skills/context) and context fixes. Use when resolving a STUCK (diagnosis-first), auditing how a converged PR was built, or auditing a /learn memory PR. Human-driven and conversational — the trail-evaluating sibling of /evaluate-pr. Outcomes land on a branch (the PR's, or a fresh capture branch if you'll discard the PR) and reach memory via merge + /learn. Triggers - evaluate-sessions, evaluate sessions, review the build trail, diagnose stuck, audit how this was built, session observability.
72
88%
Does it follow best practices?
Run evals on this skill
Adds up to 20 points to the overall score
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Low
Low-risk findings worth noting
The canonical home for this skill is evaluate-sessions in tdg-ninja/context-specs-factory-ai
Low
Low-risk findings.
1 low severity finding. Worth noting, but not necessarily harmful.
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
This skill ingests outsider-authored free text at runtime by reading the PR comment session table (via `gh pr view ... comments`) and then using the extracted session IDs to locate and open local JSONL trace files that contain user/assistant transcript text, which is attacker-controlled free text if a user authored the PR comment or trace participants’ messages.
3a7a725
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.