implementation-plan-review — for Claude Code implementation-plan-review, community, for Claude Code, ide skills, Implementation, Review, Expert, coverage, correctness, current

v1.0.0

About this Skill

Perfect for Code Review Agents needing expert implementation plan analysis against GitHub issues and repository codebases. Expert review of an implementation plan against a GitHub issue/enhancement description (provided as a local file or a GitHub issue URL) and the current repository codebase. Use when asked to critique

Features

Implementation Plan Review (Expert)
Review an implementation plan for coverage, correctness, and fit with the current codebase. Do not
Implementation plan: a local file path.
Inputs Implementation plan: a local file path
Guides implementation-plan-review usage for AI agent workflows

# Core Topics

blockscout blockscout
[0]
[0]
Updated: 3/12/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reviewed Landing Page Review Score: 10/11

Killer-Skills keeps this page indexable because it adds recommendation, limitations, and review signals beyond the upstream repository text.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution Quality floor passed for review Locale and body language aligned
Review Score
10/11
Quality Score
60
Canonical Locale
en
Detected Body Locale
en

Perfect for Code Review Agents needing expert implementation plan analysis against GitHub issues and repository codebases. Expert review of an implementation plan against a GitHub issue/enhancement description (provided as a local file or a GitHub issue URL) and the current repository codebase. Use when asked to critique

Core Value

Empowers agents to review implementation plans for coverage, correctness, and fit with the current codebase using GitHub issues and local file paths, leveraging protocols like `gh` for authentication and network access.

Ideal Agent Persona

Perfect for Code Review Agents needing expert implementation plan analysis against GitHub issues and repository codebases.

Capabilities Granted for implementation-plan-review

Reviewing implementation plans against GitHub issues for correctness
Analyzing codebase fit for proposed implementation plans
Validating implementation plan coverage against enhancement descriptions

! Prerequisites & Limits

  • Requires `gh` authentication and network access for GitHub issue resolution
  • Needs local filesystem access for implementation plan and issue/requirements files
  • Limited to reviewing plans, does not implement code changes

Source Boundary

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

After The Review

Decide The Next Action Before You Keep Reading Repository Material

Killer-Skills should not stop at opening repository instructions. It should help you decide whether to install this skill, when to cross-check against trusted collections, and when to move into workflow rollout.

Labs Demo

Browser Sandbox Environment

⚡️ Ready to unleash?

Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.

Boot Container Sandbox

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is implementation-plan-review?

Perfect for Code Review Agents needing expert implementation plan analysis against GitHub issues and repository codebases. Expert review of an implementation plan against a GitHub issue/enhancement description (provided as a local file or a GitHub issue URL) and the current repository codebase. Use when asked to critique

How do I install implementation-plan-review?

Run the command: npx killer-skills add blockscout/mcp-server/implementation-plan-review. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for implementation-plan-review?

Key use cases include: Reviewing implementation plans against GitHub issues for correctness, Analyzing codebase fit for proposed implementation plans, Validating implementation plan coverage against enhancement descriptions.

Which IDEs are compatible with implementation-plan-review?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for implementation-plan-review?

Requires `gh` authentication and network access for GitHub issue resolution. Needs local filesystem access for implementation plan and issue/requirements files. Limited to reviewing plans, does not implement code changes.

How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add blockscout/mcp-server/implementation-plan-review. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use implementation-plan-review immediately in the current project.

Upstream Repository Material

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Upstream Source

implementation-plan-review

Install implementation-plan-review, an AI agent skill for AI agent workflows and automation. Review the use cases, limitations, and setup path before rollout.

SKILL.md
Readonly
Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Supporting Evidence

Implementation Plan Review (Expert)

Review an implementation plan for coverage, correctness, and fit with the current codebase. Do not implement.

Inputs

  • Implementation plan: a local file path.
  • Issue/requirements: either (a) a local file path, or (b) a GitHub issue number (run from the target repo so gh resolves it).

If the user provides a GitHub issue number, prefer fetching it into a local file using the bundled script (requires gh auth and network access; otherwise ask for a local issue description file):

bash
1bash .codex/skills/implementation-plan-review/scripts/fetch_github_issue.sh <issue-number> --out /tmp/issue.md

If the script reports that gh is not authenticated (exit code 3), ask the user to run:

bash
1gh auth login

Workflow

  1. Ensure repo startup constraints are satisfied:

    • In this repository, run $codex-session-bootstrap before doing any other work.
  2. Read the two inputs in full:

    • Plan file
    • Issue description file (or the fetched /tmp/issue.md)
  3. Apply strict versioning-comment policy:

    • Do not request or suggest any version bump (package version, server.json, etc.) unless the issue description explicitly requires a version bump/release/publish/tag.
    • Even if the plan changes externally-consumed surfaces (tool schemas, REST/OpenAPI, manifests), treat missing version bump steps as intentional unless the issue says otherwise.
  4. Validate codebase reality (start targeted, expand as needed):

    • Start by finding referenced modules/configs/env vars/tests with rg (fast and low-noise).
    • Prefer opening the minimal set of files first to confirm patterns and naming, but broaden freely if you suspect hidden coupling or cross-cutting behavior (e.g., shared helpers, config loading, response models, pagination, truncation).
    • If the plan touches MCP tools, REST API, docs, or tests, cross-check relevant .cursor/rules/*.mdc guidance.
    • If it improves confidence, use any other repo investigation strategy (e.g., inspect docs like SPEC.md/API.md, check tests, use git blame, or run unit tests/lint locally).

Suggested commands (adapt as needed):

bash
1rg -n "name_in_plan|function_in_plan|ENV_VAR_IN_PLAN" -S . 2rg -n "ToolResponse\\[|@mcp\\.tool\\(|log_tool_invocation" blockscout_mcp_server -S 3rg -n "ServerConfig\\(|BaseSettings\\(|BLOCKSCOUT_" blockscout_mcp_server/config.py -S 4rg -n "pytest\\.mark\\.integration|tests/integration|tests/tools" tests -S
  1. Produce the review in the required format (next section).

Required output format

Produce a review with these sections:

1) Understanding

  • Issue summary
  • Acceptance criteria (bulleted)

2) Plan ↔ Requirements coverage

  • What is covered well
  • What is missing / ambiguous

3) Codebase alignment

  • Key files/modules you inspected (with paths)
  • Assumptions in the plan that match the codebase
  • Assumptions that don’t match (explain and suggest correction)

4) Review comments (actionable)

Provide comments as a list. Each comment must include:

  • Severity: Blocker | Major | Minor | Question | Nit
  • Location: plan section/step + (when relevant) repo file/function/class
  • Problem: what’s wrong / missing
  • Recommendation: concrete change to the plan
  • Rationale: why it matters (bug risk / security / perf / maintainability)

Testing gaps rule:

  • List every specific missing/incorrect test as an actionable comment in §4.
  • In §6, provide a consolidated checklist that references those items without repeating full explanations.

5) Junior-dev readiness check

  • Missing prerequisites, commands, step ordering, “how to verify”
  • Where the plan needs more explicit detail

6) Test & rollout strategy

  • Consolidated test checklist (Unit / Integration / E2E / Negative & security / Performance & regression), referencing §4 test comments
  • Migration/rollback plan if applicable
  • Feature flags / safe rollout suggestions if applicable

Review focus checklist (use as prompts, not new requirements)

  • Coverage: every acceptance criterion mapped to plan steps.
  • Codebase alignment: paths, module structure, naming, existing helpers and patterns.
  • Edge cases & compatibility: pagination, timeouts, empty results, truncation limits, backward compatibility.
  • Security: input validation, SSRF/DNS rebinding boundaries, secrets handling, logging redaction, auth assumptions.
  • Performance/scale: API call counts, caching, pagination strategy, long-running tasks/progress updates.
  • Ops/observability: error handling, logs, metrics/telemetry/analytics implications, rollout/rollback.
  • Versioning: only comment if explicitly required by the issue description; otherwise assume omission is intentional.

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