Skip to content
cccskills
FreePublished on GitHub

review-core

Provides review-workflow scaffolding for context, evidence, and output. Use at the start of any detailed review to ensure consistent, comparable findings.

The English summary is being prepared. Showing the original description.

Run score Not tested

See how to install

Files included (1)

  • SKILL.md5.7 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

Core Review Workflow

When To Use

  • Use this skill at the beginning of any detailed review workflow (e.g., for architecture, math, or an API).
  • It provides a consistent structure for capturing context, logging evidence, and formatting the final report, which makes the findings of different reviews comparable.

When NOT To Use

  • Diff-focused analysis - use diff-analysis

Activation Patterns

Trigger Keywords: review, audit, analysis, assessment, evaluation, inspection Contextual Cues:

  • "review this code/design/architecture"
  • "conduct an audit of"
  • "analyze this for issues"
  • "evaluate the quality of"
  • "perform an assessment"

Auto-Load When: Any review-specific workflow is detected or when analysis methodologies are requested.

Required TodoWrite Items

  1. review-core:context-established
  2. review-core:scope-inventoried
  3. review-core:evidence-captured
  4. review-core:deliverables-structured
  5. review-core:findings-verified
  6. review-core:contingencies-documented

Step 1 – Establish Context (review-core:context-established)

  • Confirm pwd, repo, branch, and upstream base (e.g., git status -sb, git rev-parse --abbrev-ref HEAD).
  • Note comparison target (merge base, release tag) so later diffs reference a concrete range.
  • Summarize the feature/bug/initiative under review plus stakeholders and deadlines.

Step 2 – Inventory Scope (review-core:scope-inventoried)

  • List relevant artifacts for this review: source files, configs, docs, specs, generated assets (OpenAPI, Makefiles, ADRs, notebooks, etc.).
  • Record how you enumerated them (commands like rg --files -g '*.mk', ls docs, cargo metadata).
  • Capture assumptions or constraints inherited from the plan/issue so the domain-specific analysis can cite them.

Step 3 – Capture Evidence (review-core:evidence-captured)

  • Log every command/output that informs the review (e.g., git diff --stat, make -pn, cargo doc, web.run citations). Keep snippets or line numbers for later reference.
  • Track open questions or variances found during preflight; if they block progress, record owners/timelines now.

Record Lessons Learned (decision journal)

If this work involved rework, a failed approach, or a blocker, record it to docs/lessons-learned.md so the insight survives past the session (draft and confirm):

  • If leyline is installed, invoke Skill(leyline:decision-journal) and append a lesson entry (what_happened, what_didnt_work, root_cause, action; set phase to review). Show the draft; append on confirmation.
  • Fallback (leyline absent): append to docs/lessons-learned.md using the in-file ENTRY TEMPLATE; assign the next LL-NNN id.

Step 4 – Structure Deliverables (review-core:deliverables-structured)

  • Prepare the reporting skeleton shared by all reviews:
    • Summary (baseline, scope, recommendation)
    • Ordered findings (severity, file:line, principle violated, remediation)
    • Follow-up tasks (owner + due date)
    • Evidence appendix (commands, URLs, notebooks)
  • validate the domain-specific checklist will populate each section before concluding.

Step 5 – Verify Findings Are Grounded (review-core:findings-verified)

Every finding must be falsifiable: a citation a second pass can mechanically re-read and confirm. Findings that fail verification do not ship.

  • Use the grounded-finding schema from Skill(imbue:structured-output): each finding carries a Location (file:line) and a verbatim Anchor snippet copied from that line.

  • Write the findings to .review/findings.json (one object per finding: id, file, line, anchor, severity, category, recommendation, evidence_refs).

  • Run the verifier:

    python plugins/imbue/scripts/citation_verifier.py \
      --findings .review/findings.json --repo-root .
    

    Exit 0 means every citation resolved; exit 1 lists each finding whose path, line, or anchor did not match the source.

  • Drop or label UNVERIFIED any finding the verifier failed; only verified findings enter the report. Attach the verifier output to the evidence appendix.

  • If the script is unavailable, fall back to re-reading each cited file:line by hand and confirming the anchor text is present; note the manual fallback in the contingency section.

Step 6 – Contingency Plan (review-core:contingencies-documented)

  • If a required tool or skill is unavailable (e.g., web.run), document the alternative steps that will be taken and any limitations this introduces. This helps reviewers understand any gaps in coverage.
  • Note any outstanding approvals or data needed to complete the review.

Exit Criteria

  • All TodoWrite items complete with concrete notes (commands run, files listed, evidence paths).
  • Every reported finding carries a Location + verbatim Anchor and was confirmed by citation_verifier.py (or a documented manual re-read); no unverified findings ship.
  • .review/findings.json exists and the verifier exited 0, or every failed finding was dropped or labeled UNVERIFIED.
  • Domain-specific review can now assume consistent context/evidence/deliverable scaffolding and focus on specialized analysis.
  • Any rework, failed approach, or blocker uncovered during evidence capture is recorded to docs/lessons-learned.md (or the in-file template).

Reviews

No reviews yet. Tell others what you thought.

Comments

No login needed. Share how it worked for you, ask a question, or note where it did not run.

No comments yet. Be the first to write one.

Comments are published right away. Do not include personal information such as email addresses or phone numbers. Up to 2 URLs.

0 / 1,000 characters

This form is protected by reCAPTCHA, and the Google Privacy Policy and Terms of Service apply.

More skills from this repository

Shapes turns action-first: action leads, steps numbered, state restated. Use for ADHD-friendly output. Do not use to trim tokens; use response-compression.

The English summary is being prepared. Showing the original description.

athola/claude-night-market343Updated Oct 24, 2026

Inverts burden of proof for code additions. Use when reviewing PRs, planning refactors, or running unbloat to challenge every addition's necessity.

The English summary is being prepared. Showing the original description.

athola/claude-night-market343Updated Oct 24, 2026

Tracks per-agent token usage and flags waste in parallel dispatch. Use when evaluating parallel agent efficiency or after a multi-agent run.

The English summary is being prepared. Showing the original description.

athola/claude-night-market343Updated Oct 24, 2026

Coordinates Claude agent teams via filesystem protocol. Use when orchestrating parallel agents with task dependencies. Do not use for single-agent tasks.

The English summary is being prepared. Showing the original description.

athola/claude-night-market343Updated Oct 24, 2026

Evaluates API surface design, consistency, and exemplar alignment. Use when reviewing public API changes or before releasing a new API surface.

The English summary is being prepared. Showing the original description.

athola/claude-night-market343Updated Oct 24, 2026

Selects architecture paradigm via research before scaffolding. Use when architecture is undecided and the choice needs justification and documentation.

The English summary is being prepared. Showing the original description.

athola/claude-night-market343Updated Oct 24, 2026

See all skills by athola

Report a problem with this skill