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title, date, category, module, problem_type, component, severity, tags
| title | date | category | module | problem_type | component | severity | tags | |||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| ce-doc-review confidence scoring: anchored rubric over continuous floats | 2026-04-21 | skill-design | compound-engineering / ce-doc-review | design_pattern | tooling | medium |
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ce-doc-review confidence scoring: anchored rubric over continuous floats
Problem
Persona-based document review originally used a continuous confidence field (0.0 to 1.0) that synthesis compared against per-severity numeric gates (0.50 / 0.60 / 0.65 / 0.75) and a 0.40 FYI floor. In practice the continuous scale invited false precision: personas clustered on round values (0.60, 0.65, 0.72, 0.80, 0.85), and gate boundaries created coin-flip bands where trivial score shifts moved findings in and out of the actionable tier. The personas were not genuinely differentiating 0.65 from 0.72; the model cannot calibrate self-reported confidence at that granularity.
Symptoms surfaced in review output:
- Single personas filing 3+ findings all rated 0.68-0.72, all variants of the same root premise
- Findings at 0.65 admitted into the actionable tier on noise, not signal
- Residual concerns and deferred questions near-duplicated findings already surfaced, indicating the persona's own ordering did not distinguish "raise this" from "note this"
Reference pattern: Anthropic's anchored rubric
Anthropic's official code-review plugin (anthropics/claude-plugins-official/plugins/code-review/commands/code-review.md) solves the calibration problem with 5 discrete anchors (0, 25, 50, 75, 100) each tied to a behavioral criterion the model can honestly self-apply:
0— false positive or pre-existing issue25— might be real but couldn't verify; stylistic-not-in-CLAUDE.md50— verified real but nitpick / not very important75— double-checked, will hit in practice, directly impacts functionality100— confirmed, evidence directly confirms, will happen frequently
The rubric is passed verbatim to a separate scoring agent. Filter threshold: >= 80.
Solution adopted for ce-doc-review
Port the structural techniques — anchored rubric, verbatim persona-facing text, explicit false-positive catalog — and tune the filter threshold for document-review economics. The doc-review threshold is >= 50, not Anthropic's >= 80.
Anchor-to-route mapping
| Anchor | Route |
|---|---|
0, 25 |
Dropped silently (counted in Coverage only) |
50 |
FYI subsection (surface-only, no forced decision) |
75, 100 |
Actionable tier, classified by autofix_class |
Cross-persona corroboration promotes one anchor step (50 → 75, 75 → 100, 100 → 100). This replaces the prior +0.10 numeric boost.
Within-severity sort: anchor descending, then document order as the deterministic final tiebreak.
Files
plugins/compound-engineering/skills/ce-doc-review/references/findings-schema.json—confidenceis an integer enum[0, 25, 50, 75, 100]with behavioral definitions embedded in thedescriptionfieldplugins/compound-engineering/skills/ce-doc-review/references/subagent-template.md— the rubric section personas see verbatim, plus the consolidated false-positive catalogplugins/compound-engineering/skills/ce-doc-review/references/synthesis-and-presentation.md— anchor-based gate in 3.2, anchor-step promotion in 3.4, anchor-sorted ordering in 3.8, anchor+autofix routing in 3.7plugins/compound-engineering/agents/document-review/*.agent.md— each of the 7 personas carries a persona-specific calibration section that maps domain criteria to the shared anchorstests/pipeline-review-contract.test.ts— contract tests that assert the schema enforces discrete anchors and the template embeds the rubric
Why the threshold diverges from Anthropic
Code review and document review have different economics. Anthropic's >= 80 filter is load-bearing for code review because of three constraints that do not apply to doc review:
- Code review has a linter backstop. CI runs linters, typecheckers, and tests. The LLM reviewer is a second layer on top of automated tooling, and a second layer only adds value by being more selective. If automation already catches the 50-75 tier, the LLM surfacing it again is noise.
- Code review is high-frequency and publicly visible. Every surfaced finding becomes a PR comment. A reviewer who cries wolf 5 times gets muted. Precision dominates recall.
- Code claims are ground-truth verifiable. "The code does X" can be proven or refuted by reading it. A 75 in code review often means "I couldn't verify" — which means waiting for someone who can.
Document review inverts all three:
- Doc review IS the backstop. There is no linter that catches a plan's premise gaps or scope drift. A missed finding in the plan derails implementation weeks later.
- Doc review is low-frequency and private. One review per plan, not per PR. Surfaced findings are dismissed with a keystroke via the routing menu; they are not public commentary.
- Premise claims have a natural confidence ceiling. "Is the motivation valid?" and "does this scope match the goal?" cannot be verified against ground truth. Personas working in strategy, premise, and adversarial domains (product-lens, adversarial) legitimately cap at anchors 50-75 because full verification is not possible from document text alone. A
>= 80filter would silence those personas.
Filter at >= 50 for doc review; let the routing menu handle volume. Dismissing a surfaced finding is cheap; missing a real concern is expensive.
When to port this pattern
- Other persona-based review skills with similar economics (no linter backstop, one-shot consumption, dismissal cheap via routing). Default threshold for such skills:
>= 50. - Any scoring workflow where the model is asked to self-report confidence on a continuous scale and clustering on round numbers is observed.
When NOT to port directly
- Code review workflows have linter backstops and public-comment costs. Port the rubric structure, but tune the threshold higher (
>= 75). See the "ce-code-review migration" section below for the completed port. - High-throughput pipelines where the
25anchor ("couldn't verify") represents most findings. Dropping everything below50may be too aggressive; consider surfacing25as "needs human triage" instead.
Migration history
Landed in a single atomic change because the schema, template, synthesis, rendering, personas, and tests are coupled — a partial migration would have failed validation at every boundary. The schema change is the load-bearing commit; the persona updates and test updates consume it.
Evaluation
After the migration, an A/B evaluation compared baseline (continuous float) against treatment (anchored integer rubric) across four documents spanning size and type: a 7KB in-repo plan, a 63KB in-repo plan, a 27KB external-repo plan, and a 10KB in-repo brainstorm. Both versions were executed by orchestrator subagents reading their matching skill snapshot as prompt material, dispatching all 7 personas, and emitting the Phase 4 headless envelope. The workspace, per-run envelopes, and timing data live under .context/compound-engineering/ce-doc-review-eval/ during the evaluation.
Confirmed effects
- Score dispersion collapsed. Baseline produced 7-12 distinct float values per document (typical: 0.45, 0.50, 0.55, 0.65, 0.72, 0.80, 0.85) — the exact false-precision clustering the migration targeted. Treatment concentrated on 2-3 anchors per document. Anchors
0and25were never emitted by any persona, which matches the template's "suppress silently" instruction for those tiers. - Cross-persona +1 anchor promotion fires as specified. Observed on cli-printing-press plan (security-lens + feasibility promoting an IP-range-check finding to anchor 100) and interactive-judgment plan (product-lens + adversarial promoting a premise finding to anchor 100).
- Chain linking, safe_auto silent-apply, FYI routing, and per-persona redundancy collapse all exercised correctly on at least one run.
- The
>= 50threshold is load-bearing on large plans. On cli-printing-press, baseline's graduated per-severity gates admitted 13 Decisions; treatment admitted 21. Inspection of the delta confirmed the new findings were genuine concerns the old gates' coin-flip behavior at boundaries was suppressing — not noise. The migration doc's prediction that "missing a real concern is expensive" held in practice.
Anchor-75 calibration boundary discovered
The evaluation surfaced a boundary issue: on large plans, personas emitted anchor 75 for premise-strength concerns ("motivation is thin," "premise is unconvincing") whose "will be hit in practice" claim was the reviewer's reading, not a concrete downstream outcome. This inflated the actionable tier with strength-of-argument critique that was more appropriately observational.
The subagent template's anchor 75 bullet was refined with a calibration paragraph:
Anchor
75requires naming a concrete downstream consequence someone will hit — a wrong deploy order, an unimplementable step, a contract mismatch, missing evidence that blocks a decision. Strength-of-argument concerns ("motivation is thin," "premise is unconvincing," "a different reader might disagree") do not meet this bar on their own — they are advisory observations and land at anchor50unless they also name the specific downstream outcome the reader hits.
The test the template adds: "will a competent implementer or reader concretely encounter this, or is this my opinion about the document's strength?" The former is 75; the latter is 50.
Re-evaluation with the tightened criterion shifted cli-printing-press from 21 Decisions/4 FYI to 10 Decisions/23 FYI — premise-strength concerns moved to observational routing. The change was not a blanket suppression of premise findings: on interactive-judgment plan, the premise challenge survived the tightening and got cross-persona-promoted to anchor 100, because its concrete consequence was explicit ("8-unit redesign creates maintenance debt across three reference files if the premise is wrong"). The refinement distinguishes grounded premise challenges from hand-wavy framing critique — which is the exact precision the rubric was meant to have from the start.
Limitations
- Small corpus. Four documents is enough to confirm macro patterns (clustering, severity inflation, feature coverage) but not to tune threshold values or anchor boundaries at finer granularity.
- Harness drift between iterations. Iteration-1 orchestrators dispatched parallel persona subagents; iteration-2 orchestrators executed personas inline (nested Agent tool unavailable in that session). This affected side metrics (proposed-fix count on cli-printing-press iteration-2 dropped 15 → 4, likely harness-driven rather than tweak-driven) but did not obscure the tweak's core effect, which was large-magnitude.
- No absolute-calibration ground truth. The evaluation measured the migration's stated failure modes disappearing. Whether an anchor-75 finding literally hits 75% of the time remains unmeasured; no labeled doc-review corpus exists.
ce-code-review migration (2026-04-21)
Ported the same anchored-rubric structure into ce-code-review and bundled it with three additional code-review-specific precision controls. The two skills now share calibration discipline but diverge on threshold and on how independent verification is implemented.
Threshold: >= 75 (not >= 50 like ce-doc-review, not >= 80 like Anthropic)
ce-code-review uses anchor 75 as the gate. P0 findings escape at anchor 50.
>= 75 matches the ce-doc-review choice of using the anchor itself as the threshold (no awkward middle-bucket gap). At >= 75, anchors 75 ("real, will hit in practice") and 100 ("verifiable from code alone") survive; anchors 0/25/50 are dropped. Anthropic's >= 80 under a discrete {0,25,50,75,100} scale would collapse to "anchor 100 only," which is too narrow — it would silence findings where personas can construct the trace but cannot literally read the bug off the code.
The threshold divergence from ce-doc-review (>= 50) is correct for the same reasons documented in the "Why the threshold diverges from Anthropic" section above, applied in reverse: code review HAS a linter backstop, IS publicly visible, and code claims ARE ground-truth verifiable. Code review wants narrow precision; doc review wants broad surfacing.
Validation pass (Stage 5b): the deferred follow-up, now landed
The ce-doc-review plan deferred a "neutral-scorer second pass" to a follow-up plan. ce-code-review implements it as Stage 5b: an independent validator sub-agent per surviving finding, mode-conditional dispatch, and a 15-finding budget cap.
- Why now for code review, not doc review: code review has externalizing modes (autofix applies fixes, headless returns findings to programmatic callers) where false positives have real cost — wrong fixes get committed, downstream automation acts on bad signal. Doc review's worst case is a noisy report a user dismisses with a keystroke; code review's worst case is a wrong-fix PR getting merged.
- Mode-conditional dispatch: validation runs in
headless,autofix, and the interactive LFG/File-tickets routing paths. It is skipped in interactive walk-through (the human is the per-finding validator) and report-only (nothing is being externalized). This scopes cost to the cases where false positives have real cost. - Per-finding parallel dispatch, not batched: independence is the design point. A single batched validator looking at all findings together pattern-matches across them and recreates the persona-bias problem we are escaping. Per-file batching is left as a future optimization for reviews with many findings clustered in few files.
- No
validatedfield on findings: an early plan added avalidated: booleanfield; it was removed during planning. Surviving findings post-validation are validated by definition (rejected ones are dropped); in modes where validation does not run, the run's mode tells consumers everything they need. A field constant within any mode does no work. - Conservative failure mode: validator timeout, malformed output, or dispatch error → drop the finding. Unverified findings should not externalize.
The validator's protocol is { "validated": true | false, "reason": "<one sentence>" } answering three questions: is the issue real, is it introduced by THIS diff, and is it not handled elsewhere. Template: references/validator-template.md.
Mode-aware false-positive demotion
ce-code-review's broader persona surface (17 reviewers vs ce-doc-review's 7) means more weak general-quality signal. Stricter precision in externalizing modes was already accomplished by the higher threshold; for interactive mode, a different policy: route weak findings to existing soft buckets (testing_gaps, residual_risks, advisory) rather than suppress.
The demotion rule is intentionally narrow: severity P2 or P3, autofix_class advisory, contributing reviewer is testing or maintainability. Headless and autofix suppress these entirely; interactive and report-only demote them to soft buckets where they remain visible without competing for primary-findings attention.
This is the "tier the precision bar by mode" framing. Synthesis owns it; personas don't change what they flag based on mode.
Lint-ignore suppression
Code carrying an explicit lint disable comment for the rule a reviewer is about to flag (eslint-disable-next-line no-unused-vars, # rubocop:disable Style/..., # noqa: E501, etc.) — suppress unless the suppression itself violates a project-standards rule. The author already chose to suppress; re-flagging via a different reviewer creates noise and ignores their decision.
This is the only entirely new false-positive category in ce-code-review's catalog; the rest were ported from the existing pre-anchor catalog.
PR-mode skip-condition pre-check
Before running the full review on a PR, a single gh pr view call probes for skip conditions:
- Closed or merged PR
- Draft PR
- Trivial automated PR (conservative
chore(deps)/build(deps)/ release-bump pattern with empty body) - Already has a ce-code-review report comment
Skip cleanly without dispatching reviewers. Standalone branch and base: modes always run — the skip-check is PR-mode only. Already-reviewed detection deliberately ignores commits-since-comment; the escape hatch for "I want to re-review after pushing more commits" is branch mode or base: mode, both of which bypass the skip-check entirely.
This avoids the wasted multi-agent review cost on PRs that should not be reviewed (closed, draft, dependabot-style, or already-reviewed). It is the cheapest mechanism in this migration and disproportionately valuable for any team that runs the skill against arbitrary PR queues.
Files
plugins/compound-engineering/skills/ce-code-review/references/findings-schema.json—confidenceis integer enum[0, 25, 50, 75, 100]with code-review-specific behavioral definitions in the description;_meta.confidence_anchorsand_meta.confidence_thresholdsdocument the anchors and>= 75gateplugins/compound-engineering/skills/ce-code-review/references/subagent-template.md— verbatim 5-anchor rubric with code-review framing, expanded false-positive catalog including lint-ignore rule, hard schema-conformance constraints rejecting floatsplugins/compound-engineering/skills/ce-code-review/references/validator-template.md— Stage 5b validator subagent promptplugins/compound-engineering/skills/ce-code-review/SKILL.md— Stage 5 anchor gate and one-anchor promotion (replaces+0.10), Stage 5 step 7c mode-aware demotion, Stage 5b validation pass with budget cap, Stage 1 PR-mode skip-condition pre-check, After-Review options B and C invoke validation before externalizingplugins/compound-engineering/agents/ce-*-reviewer.agent.md— 18 personas updated from float bands to anchored language, preserving each persona's specific calibration signalplugins/compound-engineering/skills/ce-code-review/references/review-output-template.md— Confidence column renders as integer (75,100), not floattests/review-skill-contract.test.ts— schema, synthesis, validation pass, skip-conditions, mode-aware demotion, and per-persona anchored-language assertions
When to apply this combined pattern to a new skill
Apply the full bundle (anchored rubric + validation pass + mode-aware demotion + skip-conditions + lint-ignore) when all of:
- The skill is a multi-persona review workflow producing structured findings.
- The skill has externalizing modes — outputs that get acted on without further human review (PR comments, autofix, downstream automation, headless callers).
- The skill is invoked frequently enough that wasted runs are visible (skip-conditions are pure win in this case; modest cost in low-volume cases).
Apply only the anchored rubric (the ce-doc-review subset) when:
- The skill is single-shot or dismissal is cheap via UI/menu — validation pass adds cost without protecting anything that wasn't already going to be triaged by a human.
- The skill operates on premise/strategy claims that lack ground-truth verification — anchor 100 is unreachable; threshold should be
>= 50.
Skip the entire pattern when:
- The skill produces a single value, not a population of findings.
- The skill operates on user input where the user IS the source of truth (e.g., interactive Q&A skills).
Migration history (ce-code-review)
Landed in a single PR with anchored rubric, validation pass, skip-conditions, mode-aware demotion, lint-ignore suppression, and persona sweep all together. The schema change is the load-bearing commit; subagent template, synthesis, and persona updates consume it. Branch: refactor/ce-code-review-precision-and-validation. The plan with full decision rationale lives at docs/plans/2026-04-21-002-refactor-ce-code-review-precision-and-validation-plan.md.
Deferred follow-ups
- PR inline comment posting mode for ce-code-review. Anthropic's plugin posts findings as inline GitHub PR comments via
mcp__github_inline_comment__create_inline_commentwith full-SHA link discipline and committable suggestion blocks. ce-code-review currently has no PR-comment mode at all (terminal output, fixer auto-apply, or headless return only). Real workflow gap; deferred because it is a substantial new mode (link format, suggestion-block handling, deduplication semantics, tracker integration overlap). - Per-file validator batching. When real-world reviews routinely surface many findings clustered in few files (large refactors), a per-file validator that reads the file once and evaluates all findings against it could meaningfully reduce cost while preserving cross-file independence. Implement when data shows the saving matters.
- Haiku-tier orchestrator-side checks. ce-code-review currently uses sonnet for all subagent dispatch including the cheap PR skip-condition probe. Push obvious cheap checks (skip-conditions, standards path discovery) to haiku.
- Re-evaluate which always-on personas earn their noise. ce-code-review keeps
testingandmaintainabilityalways-on with mode-aware demotion as the safety valve. If real review runs show the demotion is firing constantly, consider making them conditional rather than always-on.