Reviews planning documents for clarity and structure before implementation begins.

Install

mkdir -p .claude/skills/planning-reviews && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/13066" && unzip -o skill.zip -d .claude/skills/planning-reviews && rm skill.zip

Installs to .claude/skills/planning-reviews

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Run required planning-phase reviews, including human readability review, and log dispositions in the current plan artifact. Use after Implementation stage before plan approval.
176 charsno explicit “when” trigger
Advanced

Key capabilities

  • Run planning-phase review passes
  • Update the Planning Reviews section with findings and dispositions
  • Judge both structure and meaning of the plan
  • Perform a lightweight repo-anchored spot-check before reviews
  • Identify relevant review domains (e.g., security/privacy, database)
  • Provide evidence hooks for safety and trust-boundary assertions

How it works

The skill runs review passes on the plan, judges its structure and meaning, performs a spot-check, identifies review domains, and records findings and dispositions.

Inputs & outputs

You give it
A project plan after the Implementation stage
You get back
Updated Planning Reviews section in the plan artifact with findings and dispositions

When to use planning-reviews

  • Verify project plan
  • Check plan readability
  • Log plan review dispositions

About this skill

/planning-reviews

Purpose

Run planning-phase review passes and update the Planning Reviews section with findings and dispositions. Reviews must judge both structure and meaning: a structurally complete plan still fails if a maintainer or zero-contact implementation agent cannot understand what is being built, why, and how to verify it. Do not write the plan artifact directly.

Authority contract lens

  • Markdown plan artifacts are the authoring write surface.
  • Compiled registry YAML, when used, is a derived machine-readable package for validator inputs and projection metadata; it is not independent authoring authority.
  • GitHub issues, PRs, and checks are the execution truth.
  • GitHub Projects v2, rendered overlays, and runtime-mirror outputs are downstream or derived evidence surfaces only.
  • Review packaging must preserve these boundaries; no review may treat markdown as execution-authoritative once registry-first is active.
  • Authority/projection/dispatch language belongs in execution sections and appendices. If it crowds out the product/system problem or technical narrative, emit a Human Readability finding.

Finding severity labeling

  • If a review point is optional and does not block correct implementation, prefix the finding text with Non-blocker: (keep schema and ids unchanged).

User experience rule (no "go read the plan")

  • Any review material the user must act on (findings + dispositions) must be included directly in the chat response (paste the findings list and the disposition items you are asking the user to confirm).
  • Do not require the user to open the plan artifact to see what the reviewers wrote.

Q/A loop (inline)

  • The orchestrator runs the Q/A loop inline with the user only for findings that still require human agency after auto-remediation.

Evidence and specialist review routing (pre-review) (required)

Planning reviewers are plan-only by default, so they can miss repo facts unless the plan records them. Before running the review set, perform a lightweight repo-anchored spot-check and write a short summary into the plan (recommended location: ## Context Snapshot -> ### Dynamic Review Roster).

Scope (keep it fast + deterministic)

  • Read the files and components named by ## Context Snapshot, ## Technical Plan, and ## Implementation Plan.
  • Identify which review domains are actually in scope: security/privacy, cloud/provider infrastructure, database/migrations, data integrity/concurrency, API/contracts, external effects/governance, cost/operations, UI/operator workflow, domain expertise, and automation/runtime dispatch.
  • If infrastructure, hosting, auth, data deletion, external effects, or provider trust boundaries are undecided, record that explicitly and do not require provider-specific gates.
  • Optional follow-ons only if the first pass finds risk: auth providers, error handling/logging, secret loading, webhook handlers, migration/delete paths, deployment workflow files, API clients, data models, operator UI flows, and external-effect commands named by the repo.

Output shape (must be copy/pasteable into the plan)

Return a block like this (do not include secrets):

### Dynamic Review Roster (Refreshed: YYYY-MM-DD)
- Triggered specialist reviews:
  - Review: security/privacy
    - Why triggered:
    - Specialist/persona:
    - Evidence hooks (named gates or source checks):
    - Status:
  - Review: <domain>
    - Why triggered:
    - Specialist/persona:
    - Evidence hooks (named gates or source checks):
    - Status:
- Reviews considered but not triggered:
  - Review: <domain>
    - Why not triggered:

Evidence hooks (required)

For any safety, trust-boundary, data-handling, migration, external-effect, or provider-specific assertion, provide at least one named gate or source check that makes the claim executable:

  • Gate name (G-SEC-...)
  • Where it runs (CI | Local | Deployed)
  • Entrypoint/command or concrete check (not “run smoke tests”)
  • Green means (explicit pass condition)

If you cannot provide an evidence hook, emit a finding with Remediation target: Implementation and require a Decision boundary or DR-backed Defer with trigger.

Auto-remediation policy (coherent + enforceable)

  • Findings are inputs to a remediation loop before asking the user for A/R/D.
  • Tag each finding with a remediation target in the finding text: Remediation target: <Problem | Feature | Technical | Implementation | Context Snapshot | Decision Log | Unknown>.
  • Auto-remediation is allowed only when the finding is purely missing clarity/structure and remediation does not change decisions (e.g., add missing outline, add missing schema description, add missing test matrix shape, clarify a step).
  • Auto-remediation is NOT allowed when the finding touches policy/compliance/cost/trust boundaries, introduces/changes a decision boundary, or changes the stated data-handling posture. Those must be surfaced to the user for explicit A/R/D.
  • If the target is Unknown or requires external policy/source/approval, it must be surfaced to the user.
  • Deduplicate similar findings across reviews into a single remediation action.
  • After remediation, present only: what changed + remaining human-agency findings.
  • Dispositions must still be recorded for every finding:
    • Auto-Accept OK only for non-human-agency findings that were auto-remediated as documentation/structure improvements.
    • Explicit user A/R/D required for human-agency findings (policy/compliance/cost/trust boundary, decision boundary, external approval/source, or Unknown target).

Required response format (post-remediation)

  1. Remediations applied: 3-7 bullets summarizing what changed in the plan.
  2. Human decisions required (if any): list only the remaining finding ids with a 1-line explanation each.
  3. Dispositions needed: prompt only for the remaining ids (A/R/D), not for auto-remediated items.

Human Readability Review (required)

Run this review after TechnicalClarity and refresh it whenever Intent Model, Problem Definition, Technical Plan intro, Implementation Plan summary, or execution/authority sections materially change.

Review questions

  • Can a new engineer explain what is being built and why after reading only Intent Model, Problem Definition, and Technical Plan Intro?
  • Does the rendered HTML, or the markdown if HTML is not generated, read like a product/engineering plan instead of a validator report?
  • Are automation, source-of-truth, projection, dispatch, and authority-contract details confined to execution sections/appendices unless they are the actual product/system being changed?
  • Does the plan identify the strongest remaining ambiguity, or explicitly state that none remains?

Rendered HTML check

  • Prefer generating/reviewing the plan through plan-to-html when that skill/script is available.
  • If rendered HTML is unavailable, perform the same reader review over the markdown and record that HTML rendering was not run.

Use the Human readability review schema below.

Review freshness + packaging outputs

  • Tie review freshness to the current validator/package outputs for the plan state being reviewed.
  • If review packaging, validator evidence, or refreshed stamps no longer match the current plan state, treat the review as stale and rerun it.
  • In registry-first, package contradictions against authority boundaries and validator outputs rather than against a markdown-only planning model.
  • For new or refreshed reviews, record both:
    • RefreshedAt: YYYY-MM-DDTHH:MM:SS
    • ReviewedPlanHash: sha256:<hash of current plan content excluding ## Planning Reviews>
  • Date-only Refreshed: YYYY-MM-DD is legacy context only; do not use it as the freshness proof for new reviews.

Finding Closure Protocol (required)

  • After remediation, rewrite the original finding line while keeping the same F-xxx id:
    • Use (Resolved) prefix when remediated: F-012: (Resolved) <original finding summary> ...
    • Or use Non-blocker: when it is explicitly non-blocking and will not be remediated: F-013: Non-blocker: <...>
  • The plan should not look “still broken” after remediation; resolved items must be visibly marked.
  • In the assistant chat response, paste:
    • remediations applied
    • remaining human-agency findings (if any)
    • only ask A/R/D for those remaining

Review schema (must be used verbatim)

Each review must be written into the plan artifact using this exact structure so that validators and follow-on agents can reliably parse it.

Invocation note

This skill is typically invoked by /plan during the Reviews stage. Users can run it directly for debugging, but normal workflow is /plan only.

Common rules

  • Reviewers only see the current plan artifact (zero-context with respect to repo/chat).
  • Findings must be broken into the required headings for the review type.
  • Each discrete finding MUST have a stable id (F-001, F-002, ...).
  • Dispositions MUST reference finding ids and must be exhaustive: every finding is Accept, Reject, or Defer.
  • Accept requires: (1) a DR-xxx entry and (2) a patch to the relevant plan section(s).
  • Defer requires: (1) a DR-xxx entry and (2) a trigger for revisit.
  • Findings may be auto-remediated per policy above, but dispositions must still be recorded. Explicit user agency is required only for human-agency findings.

Zero-context review schema

When used for Reviews/Approved re-entry, include this block before findings:

  • Re-entry audit answers:

    • What is being built:
    • Why now:
    • Repos involved:
    • What changes first:
    • What must not happen:
    • How work is validated:
    • What remains blocked:
  • Missing context:

    • F-001: ...
  • Contradictions:

    • F-002: ...
  • Unclear decisions:

    • F-003: ...
  • Risks and edge cases:

    • F-004: ...
  • What I would screw up implementing tomorrow:

    • F-005: ...

Expert technical review schema

  • Technical risks and integrati

Content truncated.

When not to use it

  • When the plan artifact is to be written directly
  • When treating markdown as execution-authoritative once registry-first is active
  • When auto-remediation changes policy/compliance/cost/trust boundaries

Limitations

  • Do not write the plan artifact directly
  • no review may treat markdown as execution-authoritative once `registry-first` is active
  • Auto-remediation is NOT allowed when the finding touches policy/compliance/cost/trust boundaries

How it compares

This workflow systematically reviews plans for clarity and completeness, including dynamic review rosters and evidence hooks, which differs from a manual, ad-hoc review.

Compared to similar skills

planning-reviews side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
planning-reviews (this skill)01moNo flagsAdvanced
pmbok-project-management389moNo flagsIntermediate
project-planner329moReviewIntermediate
spec-kit-workflow118moNo flagsIntermediate

Try saying

Example prompts that trigger this skill in your AI assistant.

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