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Found 11,835 Skills
Primarily the agent's internal-thinking skill — invoke it silently to model a problem, identify trade-offs, and decide what to do, BEFORE asking the user anything or dispatching another skill. Workflow skills call `/culture` as their step-1 reasoning pass; the agent does not surface the dialogue. Only treat this as a user-facing skill when the user has explicitly opted out of writes — phrases like "no writes", "just rubber-duck this", "let's only talk", "/culture". In the user-facing path the output is conversation; the only sanctioned artifact is an opt-in `.cheese/notes/<slug>.md` handoff slug at session end if the user asks for notes. Culture never writes to production code, never commits, never opens PRs. If the dialogue reveals real work, recommend `/mold` (fuzzy → spec) or `/cook` (clear ask → code) and stop. Before `/mold` or `/cook`.
Kandy integration. Manage data, records, and automate workflows. Use when the user wants to interact with Kandy data.
Router skill for LLMQuant portfolio workflows. Use when the user needs company profiles, thesis tracking, theme research, watchlist monitoring, or alert management.
Cross River integration. Manage data, records, and automate workflows. Use when the user wants to interact with Cross River data.
Walk through a complete GAIA benchmark→submit flow — from key resolution through HAL-compatible package generation
iSpring Learn integration. Manage data, records, and automate workflows. Use when the user wants to interact with iSpring Learn data.
Autonomous NeMo-RL research agent workflow for directed hypothesis testing and open-ended discovery. Guides agents through the full experiment lifecycle: understanding recipes and environments, wiring RL or NeMo-gym runs, launching reproducible baselines and iterations, analyzing results, preserving human oversight, and using git plus TSV logs as the research ledger. Do NOT use for: bug fixes, code review, documentation, refactoring, dependency updates, or single-file changes.
THE workflow for picking up and carrying ONE ticket/card forward, for an autonomous worker agent or for a human doing it locally. Resolves the repo's tracker from the AFK registry (~/.claude/afk.json; GitHub Projects or Linear), picks one ticket by priority, routes by status x label (interview / human walkthrough / execute), loads LEARNINGS.md as binding constraints, implements test-first, verifies end-to-end and simplifies the diff (the /go finish), then branches to a PR for the reviewer. Use when the user says "pick up <id>", "work on issue <id>", invokes /engineer, invokes /pickup, says "pickup", or at the very start of working any card.
Transition the Linear issues linked to the current branch through their workflow states (In Progress / In Review / Done) — resolve live state IDs by team name, extract issue IDs from the branch, and apply the transition idempotently. Use when starting work on an issue, when a PR opens or updates, during branch cleanup, or whenever a branch's Linear issues need their state synced. Resolves state IDs by team name (not key — keys go stale on rename), reads the team name and issue-ID prefixes from config.json, and skips any issue already at or past the target state.
Use when the user wants to build, initialize, validate, optimize, or refactor a model-powered assistant, internal tool, automation, evaluator, or workflow from a business scenario or common problem statement, including project-structure refactors or starter skeletons that may separate model setup, prompt config, and orchestration, even if the request also mentions a UI, app shell, or local model service such as Ollama, and it is still unclear whether the solution should stay a single request, add supporting capabilities, or become orchestration. The user does not need to mention Agently explicitly.
Transform research questions into constructs, design, samples, measurement, analysis, falsification, and execution plans. Use when the user asks for "design research", "can this method answer the question?", "help me create a research proposal", or requests the rw-research-design workflow. Runs without a private local workspace or preset research-lab; use user-provided material and bundled public-source methods.
AI SDLC Conventional Commit workflow. Use when an AI assistant drafts, validates, reviews, or fixes commit messages in this repository, especially when commits must include SDD spec references, validation summaries, or safe conventional commit subjects. Supports `--quick-flow` for fast assumption-driven execution and `--full-flow` for question-driven verified execution.