19,479 mods in this category, of every kind an
agent can take. Each one carries what it costs per session, what the
scan found, and whether it is the original.
Markdown-first, AI-native parent skill for one repo-level Loop9 repo-complete loop. Use when you want the parent layer to hold repo-level owner, repo truth relocation, full finding-queue completion, repo-level closure, and final deliverable-oriented verdict while dispatching only thin handoffs to env-bootstrap /…
Use when Claude wants an adversarial review, design critique, plan critique, or second-opinion debugging from Codex AND wants to engage with the findings rather than receive a one-shot report. Sets up an Epic bead, asks Codex to file each finding as a child bead, then runs a back-and-forth where Claude responds to…
Expert Claude Code skill reviewer that validates skills against official Anthropic specifications AND effectiveness for auto-invocation with deterministic scoring. Use PROACTIVELY after creating or modifying any SKILL.md file to ensure compliance with official requirements AND that the skill will actually be…
Find similar vulnerabilities and bugs across codebases using pattern-based analysis. Use when hunting bug variants, building CodeQL/Semgrep queries, analyzing security vulnerabilities, or performing systematic code audits after finding an initial issue.
Have Claude Fable 5 plan the current task, then run an automatic warm diff-review after you execute. You (the below-Fable driver — Sonnet or Opus) gather the evidence and execute; Fable is the context-blind PLANNER — one plan engagement at the start (it writes the plan, unanchored by any draft of yours), one warm…
Socratic lenses for software engineering: question batteries that examine your work from security, design, usability, test-quality, and operational-recovery perspectives — plus an orchestrator that surfaces caveats, rabbit holes, and blast radius before you build, and a memory loop that grows new lenses from your real.
★not rated 5 2mo agoA
tokens not measured
originalMIT
Generate comprehensive summaries of pull request changes by comparing the current branch to main, or by analyzing an existing PR by number. Use when the user asks to summarize changes, preview what's in a PR, or understand what work has been done. Triggers include "summarize my changes", "what's in this PR?", "give me…
Review code changes using parallel agents. Works on local diffs or open PRs. Checks project conventions, scans for bugs, verifies claims, and resolves review threads. Use when the user says "review", "review this", "review PR", "check this PR", or invokes /review.
A software architecture review workflow that scans a codebase for structural risks and measures code quality. It checks issues such as overly complex code, repeated knowledge, changes spreading across many files, circular dependencies, and distorted domain models.
AI-powered security review of code changes via /stride-security-review:security-review — diff or full-repo scans with framework rule packs for web, mobile and CI/CD. Emits SARIF with severity gating for CI, plus a considerations mode that checks a task's securityconsiderations were mitigated.
★not rated 5
changed 21d agoA
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originalMIT
Take a coding change from idea to PR at the right level of ceremony: triage the size and risk, plan it in phases, and run implementer + reviewer subagents with a quality gate between phases.
Run parallel multi-agent code review via Solo MCP — replicates the counselors tool (https://github.com/aarondfrancis/counselors) without depending on claude -p. Use when the user asks for "counselors", "second opinion", "panel of experts", "parallel review", or "multi-agent analysis" — fan the same task out to several…
Audit steam-games-mcp — build/test/lint gate, live MCP tool edge-case sweep (input validation, SteamID64/vanity/appid edge cases, key-gating), and source-level code review. Use when asked to test/audit the published or just-fixed steam-games-mcp package, hunt for bugs/edge cases, or repeat "the same kind of testing as…
Turnkey docs review: set up notabene on any repo — write the config, create the .notabene store, and start the review server via npx (no toolchain to install) — then run the human↔agent loop: process browser comments on your docs, apply the feedback, mark resolved, write the journal, and verify.
★not rated 5
changed 25d agoA
tokens not measured
originalMIT
At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: