Agent skill

Review Swarm

by sickn33 in sickn33/agentic-awesome-skills

Parallel read-only multi-agent review of a current git diff or explicit file scope to find behavioral regressions, security or privacy risks, performance or reliability issues, and contract or test…

MITAuto-check passedAgent Workflows

Install Review Swarm

skills CLI
$ npx skills add sickn33/agentic-awesome-skills --skill review-swarm -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install sickn33/agentic-awesome-skills review-swarm --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/review-swarm .claude/skills/review-swarm && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
review-swarm
GitHub stars
47k
Used in
1 other repo
Token cost
~1.9k tokens
SKILL.md length
1,082 words
Files
2
Skills in repo
1,497
Repo updated
First seen
Licence
MIT

At a glance

Parallel read-only multi-agent review of a current git diff or explicit file scope to find behavioral regressions, security or privacy risks, performance or reliability issues, and contract or test…

  • Works in 5 steps: Determine Scope and Intent → Launch Four Read-Only Reviewers in… → Aggregate and Filter Findings → …
  • Tasks that involve Subagents
  • SKILL.md covers When to Use, Step 1: Determine Scope and…, Step 2: Launch Four Read-Only… and Step 3: Aggregate and Filter…, plus 4 more sections
  • Calls git

What it does

Review Swarm is an agent skill from sickn33/agentic-awesome-skills. Parallel read-only multi-agent review of a current git diff or explicit file scope to find behavioral regressions, security or privacy risks, performance or reliability issues, and contract or test coverage gaps.

Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `agents/openai.yaml`).

It sits in Agent Workflows, covering Subagents and Test coverage. It works with Git. The repository describes itself as: AAS Core is the local, agent-first control plane for complete catalog discovery, agent-owned selection, stack validation, and planning, backed by 2,400+ agentic skills. Includes… The licence is MIT.

When your agent uses it

  • Tasks that involve Subagents
  • Tasks that involve Test coverage

Example prompts

  • “/review-swarm”

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Determine Scope and Intent
  2. Launch Four Read-Only Reviewers in Parallel
  3. Aggregate and Filter Findings
  4. Order the Output
  5. Recommend a Clear Path Forward

What it can do on your machine

Read from SKILL.md and the folder at commit b84d35a. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • git

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use git, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Review Swarm loads about 1.9k tokens when it runs. Until then it costs about 56 tokens; SKILL.md has 1,082 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~56
When it runs · the whole SKILL.md, loaded when a task matches
~1.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from sickn33/agentic-awesome-skills at commit b84d35a, republished under its MIT licence (© sickn33). 1,082 words, ~1,897 tokens.

Download SKILL.mdSave it as .claude/skills/review-swarm/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
review-swarm
description
Parallel read-only multi-agent review of a current git diff or explicit file scope to find behavioral regressions, security or privacy risks, performance or reliability issues, and contract or test coverage gaps.
risk
safe
source
https://github.com/Dimillian/Skills/tree/main/review-swarm
source_repo
Dimillian/Skills
source_type
community
date_added
2026-07-01
license
MIT
license_source
https://github.com/Dimillian/Skills/blob/main/LICENSE

Review Swarm

When to Use

Use this skill when you need parallel read-only multi-agent review of a current git diff or explicit file scope to find behavioral regressions, security or privacy risks, performance or reliability issues, and contract or test coverage gaps. Use when the user asks for a review swarm, parallel review, diff review,...

Review a diff with four read-only sub-agents in parallel, then have the main agent filter, order, and summarize only the issues that matter. This skill is review-only: sub-agents do not edit files, and the main agent does not apply fixes as part of this workflow.

Step 1: Determine Scope and Intent

Prefer this scope order:

  1. Files or paths explicitly named by the user
  2. Current git changes
  3. An explicit branch, commit, or PR diff requested by the user
  4. Most recently modified tracked files, only if the user asked for a review and there is no clearer diff

If there is no clear review scope, stop and say so briefly.

When using git changes, choose the smallest correct diff command:

  • unstaged work: git diff
  • staged work: git diff --cached
  • mixed staged and unstaged work: review both
  • explicit branch or commit comparison: use exactly what the user requested

Before launching reviewers, read the closest local instructions and any relevant project docs for the touched area, such as:

  • AGENTS.md
  • repo workflow docs
  • architecture or contract docs for the touched module

Build a short intent packet for the reviewers:

  1. What behavior is meant to change
  2. What behavior should remain unchanged
  3. Any stated or inferred constraints, such as compatibility, rollout, security, or migration expectations

If the user did not state the intent clearly, infer it from the diff and say that the inference may be incomplete.

Step 2: Launch Four Read-Only Reviewers in Parallel

Launch four sub-agents when the scope is large enough for parallel review to help. For a tiny diff or one very small file, it is acceptable to review locally instead.

For every sub-agent:

  • give the same scope and the same intent packet
  • state that the sub-agent is read-only
  • do not let the sub-agent edit files, run apply_patch, stage changes, commit, or perform any other state-mutating action
  • ask for concise findings only
  • ask for: file and line or symbol, issue, why it matters, recommended follow-up, and confidence
  • tell the sub-agent to avoid nits, style preferences, and speculative concerns without concrete impact
  • tell the sub-agent to send findings back to the main agent only

Use these four review roles.

Sub-Agent 1: Intent and Regression Review

Review whether the diff matches the intended behavior change without introducing extra behavior drift.

Check for:

  1. Unintended behavior changes outside the stated scope
  2. Broken edge cases or fallback paths
  3. Contract drift between callers and callees
  4. Missing updates to adjacent flows that should change together

This sub-agent is read-only. It must not edit files, apply patches, or make any other workspace changes.

Recommended sub-agent role: reviewer

Sub-Agent 2: Security and Privacy Review

Review the diff for security regressions, privacy risks, and trust-boundary mistakes.

Check for:

  1. Missing or weakened authn or authz checks
  2. Unsafe input handling, injection risks, or validation gaps
  3. Secret, token, or sensitive data exposure
  4. Risky defaults, permission expansion, or trust of unverified data

This sub-agent is read-only. It must not edit files, apply patches, or make any other workspace changes.

Recommended sub-agent role: reviewer

Sub-Agent 3: Performance and Reliability Review

Review the diff for new cost, fragility, or operational risk.

Check for:

  1. Duplicate work, redundant I/O, or unnecessary recomputation
  2. Added work on startup, render, request, or other hot paths
  3. Leaks, missing cleanup, retry storms, or subscription drift
  4. Ordering, race, or failure-handling problems that make the change brittle

This sub-agent is read-only. It must not edit files, apply patches, or make any other workspace changes.

Recommended sub-agent role: reviewer

Show full SKILL.md (438 more words)Show less
Sub-Agent 4: Contracts and Coverage Review

Review the diff for compatibility gaps and missing safety nets.

Check for:

  1. API, schema, type, config, or feature-flag mismatches
  2. Migration or backward-compatibility fallout
  3. Missing or weak tests for the changed behavior
  4. Missing logs, metrics, assertions, or error paths that make regressions harder to detect

This sub-agent is read-only. It must not edit files, apply patches, or make any other workspace changes.

Recommended sub-agent role: reviewer

Report only issues that materially affect correctness, security, privacy, reliability, compatibility, or confidence in the change. It is better to miss a nit than to bury the user in low-value noise.

Step 3: Aggregate and Filter Findings

The main agent owns synthesis. Treat sub-agent output as raw review input, not final output.

Merge findings across all four reviewers and filter aggressively:

  • drop duplicates
  • drop weak or speculative claims
  • drop issues that conflict with the stated intent
  • drop minor style or readability comments unless they hide a real bug or maintenance risk

Normalize surviving findings into this shape:

  1. File and line or nearest symbol
  2. Category: regression, security, reliability, or contracts
  3. Severity: high, medium, or low
  4. Why it matters
  5. Recommended fix or follow-up
  6. Confidence: high, medium, or low

If a reviewer may be correct but the intent is unclear, turn it into an open question instead of a finding.

Step 4: Order the Output

Present findings in this order:

  1. High-severity, high-confidence issues
  2. Medium-severity issues that are likely worth fixing before merge
  3. Lower-severity issues or follow-ups that can wait

Keep the review concise. Findings should be actionable and evidence-backed.

If there are no material issues, say that directly instead of manufacturing feedback.

Step 5: Recommend a Clear Path Forward

After the findings, give the user a short path forward:

  • what to fix before merge
  • what to improve if time permits
  • what can safely be left alone

When helpful, group the path forward into:

  • fix now
  • fix soon
  • optional follow-up

Do not implement fixes as part of this skill. The output is a read-only review plus a prioritized recommendation.

Example

User request:

Use @review-swarm for this task: Parallel read-only multi-agent review of a current git diff or explicit file scope to find behavioral regressions, security or privacy risks, performance or reliability issues, and contract or test coverage gaps.

Limitations

  • Use this skill only when the task clearly matches its upstream source and local project context.
  • Verify commands, generated code, dependencies, credentials, and external service behavior before applying changes.
  • Do not treat examples as a substitute for environment-specific tests, security review, or user approval for destructive or costly actions.

© sickn33, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in skills/review-swarm of sickn33/agentic-awesome-skills.

  • SKILL.md
  • agents/openai.yaml

Open the folder on GitHubat commit b84d35a

Used in 1 other repository

We found 5 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in sickn33/agentic-awesome-skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Review Swarm next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Review Swarm compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Review Swarm this skillsickn33/agentic-awesome-skills47k1 repos~1.9kAutomated safety check: PassMIT
Review Workpeterkrueck/Claude-Code-Development-Kit1.4k—~3.3kAutomated safety check: PassMIT
Review SwarmDimillian/Skills4k—~1.6kAutomated safety check: PassMIT
Manual CLI Testpigweed-project/pigweed548—~4.1kAutomated safety check: PassApache-2.0
Base Comparisonstylelint-stylistic/stylelint-stylistic106—~2.2kAutomated safety check: PassCustom licence
Do Issueathola/claude-night-market341—~1.5kAutomated safety check: PassMIT

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Works with

Questions about Review Swarm

What does Review Swarm do?

Parallel read-only multi-agent review of a current git diff or explicit file scope to find behavioral regressions, security or privacy risks, performance or reliability issues, and contract or test…. Review Swarm is an agent skill from sickn33/agentic-awesome-skills. Parallel read-only multi-agent review of a current git diff or explicit file scope to find behavioral regressions, security or privacy risks, performance or reliability issues, and contract or test coverage gaps.

When should I use Review Swarm?

Review Swarm fits situations like: tasks that involve Subagents; tasks that involve Test coverage.

How do I install Review Swarm in Claude Code?

Run `npx skills add sickn33/agentic-awesome-skills --skill review-swarm -a claude-code`. Or copy the skill folder (skills/review-swarm in sickn33/agentic-awesome-skills) into .claude/skills/review-swarm in your project. Claude Code loads it when a task matches its description.

How do I install Review Swarm in Codex?

Run `npx skills add sickn33/agentic-awesome-skills --skill review-swarm -a codex`. Or copy the skill folder (skills/review-swarm in sickn33/agentic-awesome-skills) into .agents/skills/review-swarm in your project. Codex loads it when a task matches its description.

Can I use Review Swarm in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add sickn33/agentic-awesome-skills --skill review-swarm -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/review-swarm, .gemini/skills/review-swarm, .github/skills/review-swarm and .opencode/skills/review-swarm in your project.

What does Review Swarm need to run?

Going by SKILL.md and its folder, Review Swarm needs the command-line tools its instructions call (git).

Does Review Swarm access the network?

SKILL.md contains no URLs. Its commands use git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Review Swarm safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Review Swarm use?

Review Swarm is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Review Swarm use?

About 1.9k tokens (SKILL.md is roughly 7.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Review Swarm?

Skills that share tags, products or a category with Review Swarm: Review Work (peterkrueck/Claude-Code-Development-Kit, 1.4k stars), Review Swarm (Dimillian/Skills, 4k stars), Manual CLI Test (pigweed-project/pigweed, 548 stars) and Base Comparison (stylelint-stylistic/stylelint-stylistic, 106 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Review Swarm?

sickn33 (a GitHub user) maintains it in sickn33/agentic-awesome-skills, which has 47,405 GitHub stars. The repository holds 1,497 skills in this directory. The repository was last updated on October 9, 2026.

Source: sickn33/agentic-awesome-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.