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Found 3,746 Skills
Draft Terms of Service documents for web applications, SaaS platforms, and digital marketplaces.
Give AI agents eyes to see the internet — scrape Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu with zero API fees
Understanding security risks in software distribution and recognizing illegitimate software packages
Decision-grade entity research skill — produces a hypothesis-tested dossier on a specific company, person, nonprofit, or government org, not a generic profile. Forcing intake makes the user state their hypothesis upfront (what they already believe and want to verify or disprove) so the dossier tests it rather than confirms it. Output is an editable Word document (.docx) with verdict on the hypothesis, identity facts, 12-month activity timeline, network signals, reputation signals, red flags, 3-5 conversation hooks tied to specific findings, and source-provenance audit log. Uses WebSearch + WebFetch + free APIs (SEC EDGAR, GitHub, ProPublica Nonprofit Explorer) as workhorses; optional BYOK MCPs (LinkedIn, Crunchbase, Apollo, Pitchbook, SimilarWeb) enhance coverage. Triggers: 'research [company]', 'dossier on [person/company]', 'background check on [entity]', 'prep me for a meeting with [person/company]', 'due diligence on [company]', 'what should I know about [entity]', 'research [person] before I [meet/hire/invest]', 'competitor research on [company]', 'investor diligence [company]', 'interview prep for [company]'. Honors sensitivity exclusions for journalism + personal-vetting contexts.
Identify and analyze potentially malicious software distribution repositories masquerading as legitimate security software
Set up a Markdown-based local ticket management system for your project. Create task, bug, and chapter tickets in the .local/ticket/ directory, and track progress using checklists. It can be used casually since it is not managed by Git. Language and framework agnostic. Use when requested: "introduce ticket system", "task management with Markdown", "set up local ticket management", "create ticket", "create bug ticket", "create chapter", "create epic", "local ticket system", "setup ticket management".
Recognize and report malicious software distribution repositories masquerading as legitimate security tools
Create, run, and maintain API test collections using Bruno (OpenCollection YAML format and legacy Bru format). Use when the user wants to: (1) create a Bruno API test collection from scratch or from OpenAPI/Swagger specs, (2) write API request files with tests and assertions, (3) run API tests using bru CLI, (4) generate test reports (HTML, JUnit, JSON), (5) set up CI/CD pipelines (GitHub Actions) for automated API testing, (6) debug or fix failing Bruno API tests, (7) add environment configurations for API testing, (8) chain API requests with data extraction, or (9) work with any .yml/.bru Bruno collection files. Triggers on mentions of 'Bruno', 'bru CLI', 'API testing collection', 'OpenCollection', or requests to automate API testing with file-based collections.
Three modes. Session mode (default): extracts generalizable lessons from RESEARCH.md and git history at session end; lessons that imply a new or significantly changed skill are handed off to skill-creator. Personalize mode: searches the skills registry via `npx skills find`, reads the target skill(s), checks compatibility and scope overlap against installed skills, interviews the user to understand what they want and what to skip, then creates or improves skills using skill-creator. Registry mode: curates `skillpacks/skill_dictionary.yaml` and `skillpacks/presets/*.yaml` by assessing external packs, judging necessity/compatibility, and recommending subsets. Create mode: designs a brand- new skill from scratch using skill-creator. Never edits SKILL.md directly — all changes go through skill-creator's draft→test→iterate loop, human merges. Trigger phrases: "end session", "extract lessons", "personalize my skills", "integrate this skill", "update skillpack", "find a skill for", "create a skill", "improve skill", "refresh the skillpack registry", "assess this skill pack", "update skill_dictionary.yaml", "update index.yaml".
Scaffold the Mimas agent instruction file tree for any repository — AGENTS.md at root, subdomain CONTEXT.md files, and the full agents-docs/ hierarchy (a sibling of any existing docs/, kept separate so human-maintained project docs stay untouched). Every file is tailored to the repo's actual tech stack, git platform, and conventions. Use this skill whenever someone wants to set up agent instructions, onboard a repo for AI-assisted development, add AGENTS.md / CONTEXT.md files, create engineering docs for agents, or mentions "set up agentic repository" or "mimas template". Even if they just say "set up this repo for agents" or "add agent docs", this is the skill to use.
Sets up an `## Agent skills` block in AGENTS.md/CLAUDE.md and `docs/agents/` so the engineering skills know this repo's issue tracker (GitHub or local markdown), triage label vocabulary, and domain doc layout. Run before first use of `to-issues`, `to-prd`, `triage`, `diagnose`, `tdd`, `improve-codebase-architecture`, or `zoom-out` — or if those skills appear to be missing context about the issue tracker, triage labels, or domain docs.
Review generated or changed production code before it ships, using Clean Code, SOLID, DRY, KISS, YAGNI, and LLM-specific failure-mode checks in any programming language. Best used reactively after an agent writes, edits, refactors, or fixes code, before presenting, committing, or merging the result. Use when the user asks "review this PR", "is this safe to merge?", "make this cleaner", "audit this code", "refactor this", "fix this bug", or after a coding agent produced implementation code. Can also guide writing when explicitly invoked before a risky edit. DO NOT USE for factual/conceptual questions, CI/tooling config, git workflow, running/debugging tests, pure architecture discussion, prose writing, data analysis, or test-code review (use test-guard).