Agent Skills by Damian Galarza plugin
A skills library for Claude Code, Cursor and Codex: team code review, TDD, stacked PRs and repository readiness scoring
- 72 ★ on the repository
- Last commit
- MIT
Extended access
Why this level
- The skills direct the agent to run gh and git and read repository code, while the review itself executes no code
- The buffer skill queues posts in an external service with a BUFFER_API_TOKEN key
Install
- Works in
In your terminal, with SkillFoxx CLI
npx skillfoxx add plugins/agent-skills-by-damian-galarzaDetects the agents on your machine, shows the access level and pins the version.
Other ways to install
Access and checks
How we reviewExtended accessThe tool runs code or makes network calls and only reads external data.
- The skills direct the agent to run gh and git and read repository code, while the review itself executes no code
- The buffer skill queues posts in an external service with a BUFFER_API_TOKEN key
This is third-party code. Review the repository files before installing.
What it does
The repository was renamed from claude-code-workflows and keeps skills in the skills folder, while Claude Code plugins act as thin manifests on top of them. The engineering-skills bundle holds seven skills: team-code-review dispatches specialists and reports only verified findings, stacked-prs splits a large change into dependent pull requests with gh stack, conventional-comments and conventional-commits set the format for review comments and commit messages, tdd drives red-green-refactor one behavior at a time, webhook-receiver describes verified idempotent webhook handling, and legacy-code-protocol guides work on legacy code through characterization tests. The separate codebase-readiness and agent-ready plugins solve another task. The first scores a repository across eight dimensions from 0 to 100 and gives an improvement roadmap. The second creates AGENTS.md, ARCHITECTURE.md, documentation and a regression-aware quality gate. Outside the plugins stand herdr-code-review (the same review in a sibling Herdr pane, needs HERDR_ENV=1), code-snippet (a Carbon-style code image with PNG export) and buffer for queueing posts in Buffer with a BUFFER_API_TOKEN key. These three install through npx skills.
Who it is for. Developers and tech leads working through Claude Code, Cursor or Codex who want one set of practices for review, testing and repository preparation.
Good fit when
- Before merging a change you want a review by several agents where each finding is backed by code
- A large change is cut into a chain of dependent pull requests with gh stack
- A new feature is written by TDD: one test, one behavior, then refactoring
- A repository has to be scored for agent readiness and given a roadmap
- Legacy code is changed after characterization tests and by a multi-step protocol
Not a fit when
- You need tests and linters to run during review: team-code-review reads code and runs nothing, CI provides that feedback
- You want individual skills in Claude Code through one command: herdr-code-review, buffer and code-snippet are not in the plugins and install through npx skills
- You need a hard tie to one stack: webhook-receiver gives Rails examples and the other skills are language-agnostic
- You do not use GitHub: stacked pull requests work through gh stack
Example request
Review my pull request with a team of agents and show only the findings that the code supportsLimitations
- team-code-review is static: it does not run tests, linters, type checks or builds, and their results come from CI.
- Stacked pull requests use the gh stack extension and need GitHub CLI and a repository on GitHub.
- herdr-code-review requires the HERDR_ENV=1 environment variable and a running Herdr.
- buffer works only with a BUFFER_API_TOKEN key from Buffer, and code-snippet needs python3 and a browser.
- The author describes the codebase-readiness and agent-ready plugins on his own pages, and the repository holds the manifests and skills.
- Claude Code 2.1.277 and newer reads AGENTS.md directly, and older versions need checking. The license is MIT.
How to disable. A plugin is removed with /plugin uninstall engineering-skills@dgalarza-agent-skills, and codebase-readiness and agent-ready go the same way. Skills installed through npx skills are deleted together with their folders in the agent skills directory.
FAQ
How do I install Damian Galarza skills in Claude Code?
Run /plugin marketplace add dgalarza/agent-skills and /plugin install engineering-skills@dgalarza-agent-skills. The codebase-readiness and agent-ready plugins install the same way under their own names.
How is team-code-review different from a plain agent review?
It splits the work between specialists, verifies every finding against the code and reports only confirmed problems. The main agent owns scope, deduplication and severity.
Can I install a single skill without a plugin?
Yes, through npx skills add dgalarza/agent-skills with the --skill flag and the skill name. The -a cursor or -a codex flag picks the agent.
What does Codebase Readiness assess?
It scores a repository from 0 to 100 across eight dimensions, determines a band and builds an improvement plan.
Do the library skills need keys?
Not the main ones. Only the buffer skill needs a BUFFER_API_TOKEN key, and herdr-code-review requires HERDR_ENV=1.
Discussion
No questions or reviews yet.
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Comparison with similar tools
Cards that share the main search query, and how they differ.
| Tool | Official | Repository stars | Main difference |
|---|---|---|---|
| Agent Skills by Damian Galarza (this card) | no | 72 | |
| code-review-skill | no | 2,256 | a standalone code review skill, without specialist teamwork and per-finding verification |
| GitHub Stacked PRs | yes | 1,764 | stacked pull requests only, without TDD and repository scoring |
| TDD Guard | no | 2,375 | a hook that enforces TDD, with no step-by-step workflow |
README in short
The README presents the library as one set of skills for different agents and points to INSTALL.md for installation. The assess and prepare section covers Codebase Readiness and Agent Ready. The engineering section lists the seven skills of the bundle and herdr-code-review separately. The utilities section describes buffer and code-snippet, followed by contribution rules and the license.
README badge
Original SKILL.md
--- name: team-code-review description: Review an agent's own code changes or another contributor's pull request by dispatching specialist agents, verifying every finding, and reporting only evidence-backed issues. Use when the user asks for a code review, PR review, review of a diff, or a multi-agent quality audit. --- # Team Code Review Run a read-only, static, evidence-driven code review with specialist agents. The main agent owns scope, verification, deduplication, severity, editorial judgment, and the final report. Evidence comes from reading code, not executing it: the review does not run tests, linters, type checkers, or builds — CI owns that feedback loop. ## 1. Establish the review target Determine whether the target is: - **Own work:** changes produced by the current agent or agent team. - **Another contributor's pull request:** a PR authored outside the current agent team. Read the repository instructions first. Identify the exact review base and head, then inspect the complete diff and relevant surrounding code. Do not silently broaden the review to unrelated working-tree changes. If authorship is unclear, infer it from the conversation and PR metadata when available; ask only when the answer changes the workflow and cannot be discovered. Detect the application stack from repository evidence such as dependency manifests, framework configuration, and directory structure. Load any matching review profile before dispatching specialists. For a Rails application, read [references/rails.md](references/rails.md) and incorporate its applicable checks into the specialist assignments. Treat profiles as opinionated investigation guidance, not automatic findings; explicit repository instructions and documented architectural decisions take precedence. Record explicit non-goals and constraints. Keep the review read-only unless the user separately asks for fixes. Completion criterion: the review target, authorship branch, base/head, repository guidance, changed files, application stack, and applicable review profiles are known. ## 2. Dispatch the review team Use subagents when the runtime supports them. Give each specialist the same target, base/head, repository instructions, and read-only constraint. Assign non-overlapping primary lenses: 1. **Architecture and code quality** — assess whether responsibilities and abstractions are coherent; identify duplication or misplaced behavior; check for appropriate API clients, service objects, collaborators, boundaries, and reuse without demanding abstractions that the code does not yet need. 2. **Readability** — assess naming, control flow, local complexity, consistency, error handling, and whether intent is easy to recover from the code. 3. **Testing** — trace each changed behavior to meaningful coverage, including success and failure paths, boundary cases, regressions, and integration points. For HTTP behavior, check request construction, headers/authentication, serialization, response parsing, relevant status codes, malformed responses, timeouts, retries/idempotency where applicable, and network failures. Prefer behavioral tests over implementation-coupled assertions. 4. **Maintainability** — assess coupling, extension cost, dependency direction, operational burden, compatibility, observability, and likely future failure modes. 5. **Security** — trace trust boundaries and data flow; assess authentication, authorization, validation, injection, secret exposure, sensitive logging, dependency risk, unsafe defaults, and failure behavior. Do not inflate hypothetical risks beyond what the code supports. 6. **Documentation** — check public interfaces, setup/configuration, migrations, operational changes, examples, changelog/release notes, and repository architecture or runbook documentation affected by the change. Ask every specialist to return only actionable findings with: - severity, likelihood, and confidence; - exact file and tight line range; - the concrete failure mode or maintenance cost; - the specific conditions that trigger it, and evidence that a real caller, input, configuration, or schedule can produce those conditions; - evidence from the diff and relevant surrounding code; - the reasoning path that validates the claim, grounded in the cited code; - a concise remediation direction.