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Review Spd

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zhu1090093659
review-spd

Findings-first code review workflow for AI coding agents. Use when the user asks to review uncommitted changes, commits in a date range, or a branch compared to the main branch / PR-style diff. Focuses on bugs, regressions, correctness risks, missing tests, security/data-safety issues, and other behavior-changing defects.

Overview

Publisherzhu1090093659
Repositoryspec_driven_develop
Skill namereview-spd
Stars
987
Forks
101
Bundled files
3
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by zhu1090093659 on GitHub. Read the source before you install it.

Installation

Install the Review Spd AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/zhu1090093659/spec_driven_develop/tree/main/plugins/spec-driven-develop/skills/review-spd
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/zhu1090093659/spec_driven_develop.git /tmp/spec_driven_develop
mkdir -p .claude/skills
cp -r /tmp/spec_driven_develop/plugins/spec-driven-develop/skills/review-spd .claude/skills/review-spd
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Review Spd in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Review Spd on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Review Spd is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Review SPD

You are executing the Review SPD workflow: a findings-first review of changed code. Identify bugs, regressions, and behavior risks introduced by the changes. Do not turn this into a style review or a broad summary.

Configuration

ItemDefaultPurpose
Context scriptscripts/review-context.py relative to this Review SPD skill directoryCollect stable git context
Default targetUncommitted changesWorking tree + staged changes
Commit range defaultLast 3 daysOnly when the user requests commit/date review without dates
PR baseAuto-detect origin/main, origin/master, then remote default branchBase for branch-vs-main review
Output styleFindings firstFindings by severity before summaries

References: reviewer sub-agent template references/reviewer-template.md; final output format references/output-format.md.

Target Modes

Three mutually exclusive targets:

  1. Uncommitted mode (default)
  2. Commit-range mode — no explicit range → last 3 days
  3. Branch / PR mode — branch vs. main or explicit base

Conflict priority: branch specified → branch mode; else since/until → commit-range mode; else uncommitted. base applies only to branch mode. Vague requests ("review this") → uncommitted mode; "recent commits" without dates → --since "3 days ago".

Phase 1: Target Resolution

Resolve the context script from the installed Review SPD skill directory, not from the repository being reviewed:

bash
python <review-spd-skill-dir>/scripts/review-context.py
python <review-spd-skill-dir>/scripts/review-context.py --since "3 days ago"
python <review-spd-skill-dir>/scripts/review-context.py --since 2026-06-28 --until 2026-07-01
python <review-spd-skill-dir>/scripts/review-context.py --branch feature/foo
python <review-spd-skill-dir>/scripts/review-context.py --branch feature/foo --base origin/main

When reviewing this repository itself, the convenience wrapper scripts/review-context.py is also available.

Phase 2: Context Collection

Run the script with cwd = the repository under review (it cd's to the git root itself). The script only collects git context; it does not judge correctness. From its output identify: review mode and base/head, commit list (if any), changed files and diff stats, added/deleted/renamed files, and the unified diff hunks needing semantic review.

If the script reports no changes, stop and say there is nothing to review. Do not invent findings.

Phase 3: Review Planning

Classify review size:

  • Small (≤3 files, localized diff): cover Correctness + Tests.
  • Medium (multiple files / behavior-affecting): add Regression/Compatibility.
  • Large or high-risk (broad changes, auth/permissions, persistence, migrations, concurrency, caching, money, security, public APIs, generated code, config/deployment): add Security/Data Safety + Performance/Concurrency.

Prioritize behavior code, public contracts, data handling, error paths, configuration, persistence, tests. Deprioritize docs, formatting-only changes, generated files, lockfile churn unless they affect runtime behavior.

Phase 4: Sub-Agent Review

If the platform supports sub-agents, spawn focused reviewers using references/reviewer-template.md; otherwise perform the same focused reviews sequentially yourself. Coverage must not shrink without sub-agents.

Reviewer focuses:

  • Correctness / Bug Risk: logic errors, edge cases, state consistency, exception paths, invalid assumptions.
  • Regression / Compatibility: changed API contracts, config behavior, data formats, migrations, CLI behavior, backward compatibility.
  • Tests / Verification: missing tests for changed behavior, weak assertions, stale tests, untested failure modes.
  • Security / Data Safety: authorization, validation, injection, secrets, destructive operations, data loss, privacy.
  • Performance / Concurrency: async races, caching errors, resource leaks, excessive work, ordering bugs.

Each reviewer returns only evidence-backed candidate findings for its own focus.

Phase 5: Finding Consolidation

Merge reviewer outputs into one findings list:

  • Every finding must be supported by the diff or directly relevant context, with a file:line reference when possible.
  • No style preferences, speculative rewrites, or generic best practices unless they create a concrete bug risk.
  • Incomplete evidence → move to Questions or Residual Risks, not Findings.
  • Deduplicate overlaps; keep the clearest impact statement.
  • Order by severity: Critical, High, Medium, Low.

Severity guide:

  • Critical: data loss, security bypass, production outage, irreversible corruption, severe user impact likely.
  • High: clear bug/regression in a common or important path.
  • Medium: edge-path bug, compatibility break, missing validation, or test gap likely to hide regressions.
  • Low: minor bug risk, confusing behavior, narrow edge case, maintainability issue with direct defect potential.

Phase 6: Final Response

Use references/output-format.md. Findings are the primary focus: present them first, keep summaries brief, never bury a bug below a summary. No findings → explicitly state No findings and include residual risks or testing gaps.

Review Discipline

  • Think like a code reviewer, not a feature planner: does the change introduce new bugs?
  • Verify claims against code context before reporting.
  • Prefer one strong finding over many weak suggestions.
  • Do not modify files unless the user explicitly asks you to fix the findings.
  • If tests/builds are needed to validate a suspected issue, name the exact command or missing coverage.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Review Spd AI skill do?

Findings-first code review workflow for AI coding agents. Use when the user asks to review uncommitted changes, commits in a date range, or a branch compared to the main branch / PR-style diff. Focuses on bugs, regressions, correctness risks, missing tests, security/data-safety issues, and other behavior-changing defects.

Why use Review Spd on TypingMind?

Because you install it once and use it with any model. Review Spd is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Review Spd in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zhu1090093659/spec_driven_develop/tree/main/plugins/spec-driven-develop/skills/review-spd. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Review Spd?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Review Spd?

As many as you like. As long as a model supports skills, you can use Review Spd with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Review Spd AI skill free?

Yes. It is published on GitHub by zhu1090093659 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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