Findings Quality Gates

Use this compact checklist while the lead drafts findings.json. Do not launch another Agent, add a second reconciliation pass, edit the target, or repair a finding during report generation.

Inputs and Boundary

Use the resolved scope and authority, compact Step 1 baseline, three specialist briefs, analyzer JSON envelope, draft findings.json, and adjacent canvas.json only when the provider produced one. Open only a few target-owned files or command declarations named by a candidate when necessary. Do not reopen raw Sessions, Memory bodies, private caches, or broad project history, and do not rerun asset scanners.

The three specialist briefs are candidate evidence, not report truth. The analyzer owns machine facts. The lead owns selection, severity, dimension scores, candidate promotion, and prose.

Review Gates

Review the draft as a first-time user would:

Any failed gate blocks rendering even when the draft already has five findings. Inspect every reader-visible string in both JSON files; instructions that say private data must not be copied do not make an already embedded value safe.

1. Evidence eligibility: Retain only an observed consequence, an explicit governing requirement, or a deterministic present defect such as a direct secret, malformed active config, or exact same-scope collision. Count, length, search absence, similarity, unavailable evidence, detector none, and theoretical risk remain leads. Unreviewed Session or Learning Capture gaps stay in the evidence boundary. Resolve aliases to one canonical asset and discard example literals.
2. Concrete reader value: Each title names a specific observed consequence, not an internal detector, maturity concept, or abstract mechanism. The reason separates fact, inference, owner, provider, and uncertainty. Do not use a number in a title merely to imply severity. Provider-only evidence stays provider-labelled; cross-provider synthesis cannot turn one provider's absence into a project defect.
3. Fact consistency: Repeated counts come from the same canonical envelope. Different populations name their scope and measurement basis. The overview, dimensions, findings, and coverage rows do not contradict one another.
4. Asset accountability: Every authorized nonzero Rules, Skills, MCP, Memory, Agent, Hook, Command, Workflow, and Plugin surface appears in coverage. inspectedSurfaces contains only content actually opened. Exact integrity candidates are accounted for; similarity leads are not promoted. Inventory never proves selection, use, usefulness, or outcome. When Memory volume is high, require a bounded disposition for exact collisions, near matches, conflict/staleness, and unknown coverage: confirmed, metadata lead, unobserved, or deferred. Do not demand Memory-body proof outside authority; a count alone is not a disposition. An exact same-scope title collision is an ordinary Low governance finding unless corroborated current impact justifies a higher severity; near matches remain deferred. When project Skills are zero, trace every repeated Session procedure candidate through existing coverage. Two distinct comparable Episodes with no existing owner require a Low Skill-coverage finding; otherwise the draft must state the evidence reason for not promoting one.
5. Privacy: Reader output contains no secret value, raw prompt, stable Session id or analysis reference, raw or summarized prompt, user-home asset path, Memory title/path, or private cache layout. Long-session rows keep only anonymous aliases, role, duration, and aggregate failures; the review button regenerates its private packet without embedding locators.
6. Executable repair: Every command, tool, owner, and capability in an aiFixPrompt was discovered in the target or provider contract. Global, credential, production, PR, issue, or other external writes are explicit authorization preconditions. Credential repair includes revocation or rotation, but never assumes an environment-reference syntax, shell profile, restart route, or provider action before discovery and separate authority. Memory collision repair remains metadata review until same scope and bodies are verified; merge or deletion always requires separate authority. For Qoder Memory, require the discovered SearchMemory -> update_memory route; for project Wiki or Knowledge Cards, use a discovered /knowledge handoff. Never edit generated Memory files directly or substitute one owner for the other. When exact collisions coexist with many near-title leads, review a bounded batch and report the remaining count instead of embedding every title in one prompt.
7. Score discipline: Confirmed Memory or Skill integrity findings remain pending in Asset Health / Repair Progress until independent repair review. Counts, configuration, or same-window repair never earn Learning Capture or Loop Effectiveness credit. Memory credit requires retrieval, relevance, application, and a later improved outcome; Skill credit requires selection, task-relevant invocation, validation, and a later improved outcome. Enforce the Agent Work Loop Learning Capture ceilings: uncovered applicable demand stays at 59 or lower, current-task exercise without later comparison at 74 or lower, and 100 requires a later comparable improved outcome. An adequately reviewed no-candidate window does not require either asset.
8. Candidate promotion: New reports do not write summary.suggestions. A candidate that passes normal finding eligibility becomes an ordinary Low finding with the standard consequence, owner, expected output, verifier, aiFixPrompt, and dimension links. A try-existing, working-pattern, loop, or horizon opportunity without a current consequence remains deferred. Skill or Memory promotion still requires two distinct comparable Task Episodes and the observed -> built-in -> configured -> extend -> create ladder. Never invent / or $ invocation syntax.

Retain every distinct supported finding. Five is a coverage floor for a normal evidence-rich report, never a target total or deletion threshold. Keep findings beyond five when they have independent consequences or owners; only the three priority moves are ranked down. Fewer findings are valid when evidence is sparse. Reject filler, exact duplicates, and unsupported absence claims rather than deleting eligible findings for presentation density.

Stop

Render only after every gate passes and the working reconciliation accounts for each omitted candidate as an exact merge, unsupported lead, or explicit defer.