/evaluate-findings

name: evaluate-findings
description: "Critically assess external feedback (code reviews, AI reviewers, PR comments) and decide which suggestions to apply using adversarial verification. Use when the user asks to \"evaluate findings\", \"assess review comments\", \"triage review feedback\", \"evaluate review output\", or \"filter false positives\"."

Evaluate Findings

Assess external feedback (code reviews, AI suggestions, PR comments) with adversarial verification. Triage findings into actionable verdicts. Do not apply fixes.

Step 1: Assess Each Finding

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 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:

1. **Read the referenced code** at the mentioned location — include the full function or logical block, not just the flagged line 2. **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. 3. **Determine scope** — clarify whether the issue was introduced by the PR/changeset or is pre-existing.

• Pre-existing issues in earlier commits on the same feature branch are in-scope by default — the entire branch is one coherent unit of work. Judge these on their merits like any in-scope finding.
• Findings genuinely outside the branch's work are the user's call to include. Assign Escalate so the user decides whether to widen the changeset. Reserve Skip for changes whose cost wildly dwarfs the benefit.

4. **Verify the claim** against the actual code — does the issue genuinely exist?

• When the finding offers a concrete example as evidence — a claimed mishandled input, a claimed wrong output — verify that example independently: a finding can hold in substance while its example does not. Keep the finding and record the correction beside it; drop it only when the claim rests on that example alone.
• When the finding asserts a compatibility property, establish two things before assigning Apply: what the existing check actually enforces, and what real counterparts produce today. A claim stronger than the check enforces is a premise error rather than a defect — Skip, citing what the check enforces, or narrow the finding to the property it does enforce and record the narrowing beside it. When neither can be established from the code, the artifacts, or authoritative documentation, keep the finding Escalate.
• When the finding cites a rule or convention, read the cited text, then look for a place that already applied it before this changeset — the same file, or the nearest files the rule also governs. Where the text alone leaves the reading open, read the rule the way that application reads it; where no such application exists, judge on the text alone.
• When the finding rests on a premise that reading the source cannot settle — what a platform API returns at runtime, or what a value measures once the system runs — establish that premise before assigning Apply, using a targeted search or count over the source, or a measurement from a surface already running in this session. A premise of this kind reads as sound whether or not it holds, so confidence in the finding is no substitute. When nothing available settles it, keep the finding Escalate, naming the unverified premise.

5. **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.

6. **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 | | **Skip** | False positive, subjective preference, reviewer is wrong, or the change's cost wildly dwarfs its benefit | | **Escalate** | Needs the user's judgment: behavior might be intentional, involves product intent, requires domain knowledge the agent lacks, the finding is out of scope, or two findings present a genuine trade-off |

Also assign an internal confidence level — **High**, **Medium**, or **Low** — reflecting how certain you are about the verdict. Confidence is used solely to route findings to the Devil's Advocate in Step 2. It does not appear in the output.

**Escalate guidance:** When a finding questions whether behavior is intentional and neither