Pratiyush

Demonstrates extended spec features. Use when learning about security, testing, composition.

A skill with CRLF line endings. Use when testing CRLF handling.

A skill with no body content at all. Use when testing empty body parsing.

Fixture for extended spec validation tests. Use when testing extended fields.

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Max length name test.

A test skill with a .skillignore file. Use when testing filterFiles behavior.

Unicode test skill 🤖 with Chinese 你好 and Arabic مرحبا characters. Use when testing unicode handling.

Maintain project health by enforcing PR checklists, tracking open issues, verifying release readiness, and ensuring framework phases are up to date. Use when reviewing PRs, creating issues, preparing releases, or auditing project state.

Scaffold new Agent Skills with best-practice structure and frontmatter. Use when the user wants to create a new skill, bootstrap a skill directory, or generate SKILL.md boilerplate following the Agent Skills spec.

Validate CSV and JSON data files against schemas and quality rules. Use when the user asks to check data quality, validate a dataset, or verify file contents match an expected schema.

Audit project dependencies for known vulnerabilities, outdated packages, and license compliance issues. Use when the user asks to check dependencies, audit packages, review licenses, or assess supply chain security.

Generate friendly greeting messages in multiple languages. Use when the user asks for a hello message, welcome text, or localized greeting.

Maintain project release notes, changelogs, and framework phase updates. Use when the user asks to generate a changelog, draft release notes, update CHANGELOG.md, or track framework phase transitions.

Generate test file stubs and boilerplate from source code analysis. Use when the user asks to create tests, add test coverage, or scaffold test files for existing source code.

Analyze Java source files for code quality issues including style violations, complexity warnings, and common anti-patterns. Use when reviewing Java code, running quality checks, or preparing for code review.

Run the complete llmwiki pipeline from scratch — init, sync, graph, build, lint, and serve. Use when the user says "run everything", "full pipeline", "wiki-all", or wants to rebuild the entire wiki from session history.

Ingest one source document (or a folder of them) into the llmwiki. Use when the user drops a new markdown file, PDF, or URL into the wiki and asks you to process it. The user will typically say "ingest this", "add this to the wiki", "process this file into the wiki", or point at a file under `raw/`.

Answer a question by querying the user's llmwiki. Use when the user asks about their own past work — "what did I decide about X", "what have I been working on", "how did I solve Y", "what's my preferred approach to Z", or any question that the wiki (built from their session history) might answer. Always read the wiki first before falling back to external search.

Sync Claude Code session transcripts into the user's llmwiki and ingest them into the wiki. Use when the user says "sync the wiki", "update llmwiki", "ingest recent sessions", "refresh the knowledge base", or asks a knowledge question that would benefit from up-to-date sessions. Also use when the user explicitly asks to refresh or rebuild the LLM wiki from their agent history.

Maintain an llmwiki-style open-source project across the full framework pipeline. Use when the user says "maintain the project", "check my tasks", "update progress", "run phase gate", "do a monthly verify", "lint my wiki", "check stale entries", or invokes any form of ongoing project-keeping chore. Reads _progress.md, tasks.md, docs/roadmap.md, and .github issues to figure out what's next and what's drifted.

Extract reusable patterns from recent sessions, propose framework improvements, and (with approval) update the framework docs. This is the dogfooding meta-loop — the project learns from its own usage. Use when the user says "learn from this", "what did we learn", "extract lessons", "update the framework", "add this to steering rules", or after completing any substantial feature or debugging session.

One-off, operator-run skill that reverse-engineers house coding standards, conventions, and anti-patterns from a repository's git history and GitLab MR discussions, then proposes concrete edits to the sql-migration skill's artifacts. Trigger phrases like "reverse engineer conventions", "mine review comments", "audit the sql-migration flow".

One-time skill to mine the SQL migrations repo's git history and produce draft conventions.md, templates/, examples/, and anti-patterns.md for the sql-migration runtime skill. Trigger phrases like "mine SQL history", "refresh conventions", "bootstrap sql-migration artifacts".

Turn a Jira ticket into a draft GitLab MR containing a paired forward + rollback SQL migration that follows this repo's conventions. Trigger on phrases like "work <JIRA-KEY>", "create migration for ticket", "draft SQL for <KEY>".