watercooler
watercooler には mostlyharmless-ai から収集した 7 個の skills があり、リポジトリ単位の職業カバレッジとサイト内 skill 詳細ページを表示します。
このリポジトリの skills
This skill should be used to keep CLAUDE.md, AGENTS.md, and the skill files themselves compact, current, and internally consistent. It runs in three phases: Phase 1 performs a one-time structural refactor of CLAUDE.md using a Karpathy-inspired behavioral scaffold and derives AGENTS.md from it by stripping Claude Code-specific sections. Phase 2 extracts durable project conventions from Watercooler Decision entries since the last update and patches a bounded generated section. Phase 3 audits the local skill surface against the live MCP tool surface and the in-process alias registry (`TOOL_ALIASES` in `aliases.py`), surfacing skill files that reference retired or renamed tools. Use when CLAUDE.md has grown verbose or stale, when AGENTS.md has drifted from CLAUDE.md, when significant project decisions have accumulated since the last refresh, or after a watercooler-cloud tool-surface consolidation lands.
Find discussions and entries related to a specific topic or entry. Use to discover connected context across threads.
Recall project context or answer questions about history and decisions. Use before starting work, when investigating unfamiliar code, or asking "What was decided about X?" / "Why did we choose Y?"
Search threads with filters. Supports filters like role:planner, type:Decision, after:2024-01, thread:topic-name, status:OPEN
List and navigate watercooler threads. Use to see active discussions, find specific threads, or get an overview of project threads.
Check watercooler system health — MCP server, baseline graph (T1), git auth, GitHub rate limit, and daemons. Use when syncs break or anything in the watercooler stack behaves unexpectedly.
Bootstrap Watercooler memory for a repository by inspecting local code, docs, CI, git history, and existing Watercooler threads, then writing a small set of durable, provenance-backed seed threads that future agents can query and extend. Use when entering a repo for the first time, seeding a repo with Watercooler context, or refreshing foundational repository context.