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Found 29 Skills
Use when testing, reviewing, pressure-testing, refining, packaging, or validating agent skills for academic research workflows before installing or relying on them.
Evaluate Agent Skill design quality against official specifications and best practices. Use when reviewing, auditing, or improving SKILL.md files and skill packages. Provides multi-dimensional scoring and actionable improvement suggestions.
Use when a workflow, recipe, or capability needs to be packaged as an agent skill, or when an existing skill needs scaffolding, validation, linting, or evals. Covers requests to build, create, generate, scaffold, check, or evaluate a skill: a folder holding SKILL.md, scripts, tests, a task graph, CI, and eval cases. Applies even when the request says playbook, runbook, or reusable workflow instead of skill.
Evaluate a skill against the Legal Skill Design Framework — thirteen design parameters (including trust-surface, freshness, schema validation, and conflict detection), three legal failure modes, and a three-band verdict (Ready / Some Concern / Material Concerns). Use when deciding whether to trust a community skill before installing it, before deploying a first-party skill to your team, or whenever the user asks "should I trust this?" or "is this skill well-designed?". Runs automatically as part of /legal-builder-hub:skill-installer.
Evaluate Expo skills in this repo end-to-end - trigger accuracy, generated code quality, and runtime screenshots on iOS simulator and Android emulator via Expo Go (web optional). Use when the user wants to eval an Expo skill, test that a skill produces working code, benchmark a skill with device screenshots, or verify a skill's output renders correctly.
Evaluates agent skills against Anthropic's best practices. Use when asked to review, evaluate, assess, or audit a skill for quality. Analyzes SKILL.md structure, naming conventions, description quality, content organization, and identifies anti-patterns. Produces actionable improvement recommendations.
Grades a repo's agent skills by scoring agent conversations against efficiency and code-quality rubrics, then drafts concrete skill edits and a shareable report. Use when the user wants their agent setup graded from real conversation history, or asks which of their installed skills are actually working.
Designs and writes high-quality Agent Skills (SKILL.md + optional reference files/scripts). Use when asked to create a new Skill, rewrite an existing Skill, improve Skill structure/metadata, or generate templates/evaluations for Skills.
Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, update or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or iterate on skill quality. Triggers: "create a skill", "make a new skill", "build a skill for", "write a skill that", "skill for doing X", "I want a skill to", "new skill", "design a skill", "scaffold a skill", "improve this skill", "optimize this skill", "this skill isn't working well", "evaluate this skill", "score this skill", "how good is this skill", "run evals on", "benchmark this skill", "test this skill's quality", "skill quality", "skill performance". Also triggers when a user describes a repeatable workflow they want to automate, says "I keep doing X manually", "can you remember how to do X", or "turn this into a skill".
Rigorously evaluate an Agent Skill end-to-end across ANY coding-agent CLI — verify its scripts emit the documented numbers (deterministic checks), test whether its description triggers on the right prompts, and measure whether an agent following the SKILL.md beats a no-skill baseline (with/without pass-rate delta, mean ± stddev, benchmarked). Use whenever you need to test, benchmark, validate, grade, or quantify a skill's quality, check if a skill "actually works," compare two skill versions, optimize a skill's triggering, or set up an eval suite — even if the user just says "is this skill any good," "does my skill work," or "benchmark this skill." Drives Claude Code, OpenAI Codex, Antigravity (agy), Cursor, GitHub Copilot, Amp, opencode, or Grok in headless mode.
Audit existing skills with Tessl scoring, metadata and trigger-coverage checks, repo conventions, and skill-authoring best practices. Use when creating or revising a skill, triaging weak self-activation, or comparing a skill against source-repo guidance such as `AGENTS.md`, `CLAUDE.md`, or repo rules, plus external skill guidance. Do not use to verify general application code or to rewrite unrelated docs.
Comprehensive security and safety evaluation system for agent skills (.skill files). Use when users provide GitHub URLs, website links, or .skill files for download and request security assessment, safety evaluation, or ask "is this skill safe to use." Evaluates prompt injection risks, malicious code patterns, hidden instructions, data exfiltration attempts, and provides actionable recommendations with risk scoring.