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Critically assess external feedback (code reviews, AI reviewers, PR comments) and decide which suggestions to apply using adversarial verification.
Passed 13 of 18 test cases with the skill, and 5 of 18 without it.
and 8 more in the full report
11 fixed5 passed either way6 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 11 test cases the skill fixed. Same model, same prompt, with and without the skill.
After evaluating findings for our pull request, finding #1 (buffer overflow) has High confidence (Apply), while finding #2 (potential deadlock under heavy load) has Medium confidence (Apply). When triggering Step 2 (Devil's Advocate sub-agent), which findings should be passed to the sub-agent for adversarial challenge?
| Checked | Without skill | With skill |
|---|---|---|
| The response routes only finding #2 to the sub-agent. | Missed | Passed |
The instructions your model reads when the skill loads.
Assess external feedback (code reviews, AI suggestions, PR comments) with adversarial verification. Triage findings into actionable verdicts. Do not apply fixes.
If you already assessed a finding earlier in this session and recorded a verdict of Skip or Escalate — for example when an iterating loop re-runs review and the same finding resurfaces — do not re-adjudicate it from scratch. When a loop ledger path (.turbo/loops/<slug>.md) is in context, read it and treat its recorded verdicts the same way. When the re-reported finding matches one you already judged (same location and substance) and presents no new evidence beyond what your recorded reason already accounts for, keep that verdict and reason without re-reading the code, re-verifying, or routing it to the Devil's Advocate in Step 2. Assess fresh only when the finding raises materially new evidence, or when you have not judged it before in this session.
When several findings rest on a shared premise — for example a source-of-truth choice — verify that premise once before adjudicating them individually. Findings whose premise holds proceed through normal per-finding verification; when it fails, they are all Skip, citing the refuted premise.
When a plan governs the work, re-read the decisions it records before adjudicating. Having read it earlier in the session does not count: once it falls out of context, a recorded decision is indistinguishable from no decision at all.
For each finding:
Read the referenced code at the mentioned location — include the full function or logical block, not just the flagged line
Check whether the code has diverged — if the finding references code that no longer exists or has since changed, skip it and note the divergence.
Determine scope — clarify whether the issue was introduced by the PR/changeset or is pre-existing.
Verify the claim against the actual code — does the issue genuinely exist?
Assess severity:
| Severity | Meaning |
|---|---|
| Critical | Drop everything. Blocking release or operations. |
| High | Urgent. Should be addressed in the next cycle. |
| Medium | Normal. To be fixed eventually. |
| Low | Nice to have. Minor improvement. |
If the upstream reviewer already assigned a priority (P0-P3), map it: P0→Critical, P1→High, P2→Medium, P3→Low. Then re-assess based on what the actual code reveals. The upstream level is a starting point, not a binding constraint. When the re-assessed severity differs from the upstream level, note the change and the reason.
If the finding has no upstream priority, assess severity from scratch.
Assign a verdict and confidence:
| Verdict | Criteria |
|---|---|
| Apply | The finding is real and in scope: clear bug, missing check, genuine improvement, style violation matching project conventions |
test cases passed, vs 5 / 18 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.