n24q02m
UserKnowledge graph for token-efficient code reviews -- semantic search and call-graph resolution across your codebase.
Categories
Indexed Skills (41)
review-pr
Comprehensive PR review -- full branch diff against base, commit-by-commit analysis, breaking change detection, conventional commit verification.
refactor-check
Safety analysis before refactoring -- dependency graph, test coverage, public API exposure, blast radius verdict.
review-delta
Review only changes since last commit using impact analysis. Token-efficient delta review with automatic blast-radius detection.
follow-up
Find emails needing follow-up -- unanswered sent emails, flagged unreplied, draft contextual responses
inbox-review
Morning inbox workflow -- multi-account scan, thread grouping, priority classification, draft replies
compare
Structured comparison of 2+ alternatives with consistent criteria and decision matrix
fact-check
Verify a claim using adversarial search — find both supporting AND contradicting evidence
lock-project-stack
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.
research-topic
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.
build-graph
Build or update the code review knowledge graph. Run this first to initialize, or let hooks keep it updated automatically.
bulk-update
Update properties or content across many pages in a Notion database with dry-run and error recovery
organize-database
Transform unstructured Notion pages into a well-designed database with proper schema and migration
knowledge-audit
Review and clean up stored memories — find duplicates, contradictions, stale entries, and consolidate
memory-commit
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.
passport-bootstrap
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.
recall-context
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.
session-handoff
End-of-session knowledge capture — decisions, preferences, corrections, conventions, open questions
add-mechanic
Add game mechanics with correct GDScript 4.x patterns -- movement, health, inventory, save/load
build-scene
Pattern-based Godot scene construction with node hierarchy templates and companion node rules
debug-issue
Systematic Godot debugging decision trees for physics, signals, rendering, navigation, and input issues
channel-post
Compose and post formatted content to a Telegram channel -- MarkdownV2 escaping, message splitting, media ordering
setup-bot
Diagnose and fix Telegram bot connection issues -- verify config, test send, resolve common errors
refactor-check
Safety analysis before refactoring -- dependency graph, test coverage, public API exposure, blast radius verdict.
review-delta
Review uncommitted changes using impact analysis. Quick local delta review with blast-radius detection.
review-pr
Comprehensive PR review -- full branch diff against base, commit-by-commit analysis, breaking change detection, conventional commit verification.
follow-up
Find emails needing follow-up -- unanswered sent emails, flagged unreplied, draft contextual responses
inbox-review
Morning inbox workflow -- multi-account scan, thread grouping, priority classification, draft replies
bulk-update
Update properties or content across many pages in a Notion database with dry-run and error recovery
organize-database
Transform unstructured Notion pages into a well-designed database with proper schema and migration
knowledge-audit
Review and clean up stored memories — find duplicates, contradictions, stale entries, and consolidate
memory-commit
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.
passport-bootstrap
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.
recall-context
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.
session-handoff
End-of-session knowledge capture — decisions, preferences, corrections, conventions, open questions
compare
Structured comparison of 2+ alternatives with consistent criteria and decision matrix
fact-check
Verify a claim using adversarial search — find both supporting AND contradicting evidence
lock-project-stack
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.
research-topic
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.
image-describe
Describe the contents of an image file or URL in structured detail
agent-chat
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.
image-describe
Describe the contents of an image file or URL in structured detail
Bio shown is the top-scored skill's repo description as a fallback — real GitHub bios land in a future update.