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Found 255 Skills
Use this skill for Fabric.so CLI workflows with the `fabric` terminal command: diagnose/install/login, search or browse a Fabric library, save notes/links/files, create folders, ask the Fabric AI assistant, manage tasks/workspaces, generate shell completion, check subscription usage, produce JSON output, and use Fabric as persistent agent memory. Do not use for Microsoft Fabric/Azure/Power BI `fab`, Daniel Miessler's Fabric framework, Python Fabric SSH, Fabric.js, or textile/fashion fabric.
Download videos from YouTube and other platforms for offline viewing, editing, or archival with support for various formats and quality options.
Full-lifecycle AI music album production — concept, lyric drafting, track sequencing, and export. Useful for indie album experiments and brand soundtracks.
Agent skill that audits vibe-coded apps for common security vulnerabilities introduced by AI coding assistants
Use when the user asks to define a goal, create a Goal Contract, or clarify a concrete task's goal, scope, success criteria, evidence, or guardrails before planning or execution.
Research Methodology guides the agent through the complete scientific research lifecycle: hypothesis generation from literature gaps, experimental design with proper controls, systematic literature review, data collection protocols, and peer review preparation.
Run /test to write a test suite for code you just built or changed, after implementing a feature, route, or fix. Targets uncommitted changes automatically, reads test preferences.json for your framework (asks and saves it if absent), and picks the right strategy per file: happy path, edge cases, error states, accessibility.
Use when consolidating a skill from a claude-toolkit plugin or local .claude/skills into the dogfooded-skills library.
A complete, opinionated development workflow skill for agents. Triggers when the user asks to implement a feature, fix a bug, or refactor code in a Git repo. Enforces hygiene, security, quality, and atomic commits.
Author, audit, and improve Grafana SKILL.md files against Anthropic's published Agent Skills guidance and the four-dimension rubric the grafana/skills CI gate uses (conciseness, actionability, workflow clarity, progressive disclosure). Applies the canonical SKILL.md structure (YAML frontmatter + body + references/ + scripts/ + assets/), the "pushy description" trigger pattern, the three-level progressive-disclosure model, and the validate-fix-rerun feedback loop. Use when creating a new skill in this repo, when reviewing a skill PR, when a skill's Tessl review score is below 75 (the merge gate), when a skill's description isn't getting picked up by agents, when restructuring a long SKILL.md into a bundle, or when the user asks how to write, improve, optimize, audit, or fix a skill - even if they don't say "skill" explicitly (e.g. "this isn't triggering", "Tessl scored this 72", "split this doc").
Create, run, diagnose, and iteratively improve Agent Skill evaluations (evals) with the skill-up CLI / 使用 skill-up CLI 创建、运行、诊断并持续改进 Agent Skill 评测. Use when the user asks to evaluate, test, regress, verify, fix, improve, iterate, or evolve a Skill; add or strengthen eval cases; write eval.yaml/case.yaml; run skill-up run/validate/list-cases/report/import/init; or migrate from Anthropic evals.json. Handles Skill discovery, eval scaffolding, judge authoring, validation, runs, reports, and evidence-based repair loops.
Confirm a change before merge. `/check verify` drives the real app to prove behavior against the spec (every acceptance criterion met, every surface built). `/check review` runs a senior code review on a fresh model, one that did not write the code. Verify after /develop, review before a PR. Writes to docs/reviews/, never edits code.