Claude Skills by n24q02m

Use when two or more agent sessions (Claude Code or other tools, same machine or peers) must coordinate through markdown files in a shared folder instead of one supervisor driving subagents — group chat, blackboard, mailbox/inbox, multi-session handoff, or an agent-chat/ directory. Triggers include peer agents, N sessions sharing a folder, waiting for another session's reply, atomic task claiming, and needing multiple separate group chats/channels.

Blast radius of a change you have not made yet -- traces a symbol across federated repositories, splits impact per repo, and reports what must ship together.

Index an unfamiliar codebase into the knowledge graph, then produce a first orientation map -- entry points, most-depended-upon modules, hotspots, test topology.

Safety analysis before refactoring -- dependency graph, test coverage, public API exposure, blast radius verdict.

Review uncommitted changes using impact analysis. Quick local delta review with blast-radius detection.

Comprehensive PR review -- full branch diff against base, commit-by-commit analysis, breaking change detection, conventional commit verification.

Graph-driven security sweep -- scan for dangerous sinks, then rank each finding by whether an entry point can actually reach it, and triage the rest into suppressions.

Find emails needing follow-up -- unanswered sent emails, flagged unreplied, draft contextual responses

Morning inbox workflow -- multi-account scan, thread grouping, priority classification, draft replies

Add game mechanics with correct GDScript 4.x patterns -- movement, health, inventory, save/load

Pattern-based Godot scene construction with node hierarchy templates and companion node rules

Systematic Godot debugging decision trees for physics, signals, rendering, navigation, and input issues

Update properties or content across many pages in a Notion database with dry-run and error recovery

Transform unstructured Notion pages into a well-designed database with proper schema and migration

Compose and post formatted content to a Telegram channel -- MarkdownV2 escaping, message splitting, media ordering

Diagnose and fix Telegram bot connection issues -- verify config, test send, resolve common errors

Describe the contents of an image file or URL in structured detail

Review and clean up stored memories — find duplicates, contradictions, stale entries, and consolidate

Use when the user explicitly says "remember this", "save this", "ghi nho", "luu lai", "save for next time", or otherwise asks to persist the immediately preceding context. Captures with the appropriate context_type (decision, preference, fact, skill, task, conversation) so future sessions can retrieve it accurately.

Use when the user installs mnemo-mcp on a fresh machine and wants to restore prior memory state from S3 or Google Drive (Phase 2 passport sync). Triggers on phrases like "set up mnemo on this machine", "restore my memory passport", "import passport", "bootstrap mnemo", or when the user says they got a new laptop / VM and wants their memories back.

Use at session start, before significant decisions, or when a new task references a known project to recall mnemo memories matching the current working directory, recently edited files, or topic keywords. Helps maintain continuity across sessions and avoid redoing past research.

End-of-session knowledge capture — decisions, preferences, corrections, conventions, open questions

Answer time-travel questions over stored memory — what was believed at a past point in time, when a belief changed, and what replaced it. Use when the user says "as of", "back in", "at the time", "history of", "timeline", "what did I think then", or asks why a current memory contradicts an older one.

Structured comparison of 2+ alternatives with consistent criteria and decision matrix

Verify a claim using adversarial search — find both supporting AND contradicting evidence

Detect a project's manifest (pyproject.toml / package.json / go.mod / Cargo.toml), pin its library set into wet-mcp's Cabinets project_context, then route subsequent docs queries to the locked versions automatically.

Multi-step research orchestration. Use when user asks "research X", "summarize current state of Y", "what's the latest on Z", or compares approaches. Calls extract(action="agent") which searches the web, extracts top results, then synthesises a citation-preserving Markdown answer with one configured LLM.

Extract many known URLs in one polite, rate-limited pass. Use when the user hands over a list of links, a set of search hits to read in full, or asks to "scrape these pages" / "pull the content from all of them". Drives extract(action="batch"), which fans out with per-domain rate limiting and returns partial results plus a per-URL error list.