florianbuetow

This skill should be used when the user asks to "check clean code", "review code cleanliness", "find code smells", "is this function too long", "are these names clear", "review my error handling", "check my tests", or "clean up this code". Also triggers when the user mentions Clean Code, Uncle Bob, Robert Martin, meaningful names, function length, comment rot, F.I.R.S.T. tests, or names a dimension directly ("naming", "boundaries", "concurrency"). Supports auditing all nine dimensions at once or focusing on a single dimension.

Scan Claude Code chat session logs for recurring agent anti-patterns (hedging, stalling, skipping, false completions, preference-asking, dismissing, cosmetic, caveats, flagging) and produce a ranked report with frequency counts, example excerpts, and suggested guardrail rules. Use when user asks to "analyze sessions for anti-patterns", "find bad patterns in logs", "what anti-patterns am I seeing", "agent-guardrails analyze", or wants data-driven guardrail recommendations.

Install agent behavioral guardrail rules into a project's .claude/ directory. Generates a Stop hook bash script and configures settings.local.json. Includes nine battle-tested rules (no-guessing, no-stalling, no-preference-asking, no-false-completion, no-skipping, no-dismissing, no-cosmetic, no-caveats, no-flagging). Use when user asks to "install guardrails", "set up agent guardrails", "add behavioral hooks", "agent-guardrails install", or wants to enforce assistant discipline.

Test installed agent guardrail hooks by sending trigger phrases through the stop hook script. Checks hook installation first, then runs two test phrases per rule. Use when user asks to "test guardrails", "verify hooks", "check guardrail patterns", "agent-guardrails test", or wants to confirm hooks are working.

Re-analyze Claude Code session logs against existing agent guardrail rules to measure effectiveness, catch false positives, identify missed anti-patterns, and refine regex patterns. Use when user asks to "update guardrails", "refine guardrail rules", "check guardrail effectiveness", "agent-guardrails update", "tune guardrails", or wants to improve existing behavioral rules based on real usage data.

Use when the user wants to write a "product spec" or "product specification", frame a "product bet", or define a falsifiable hypothesis before building. Also triggers on "replace the PRD", "retire the PRD", "the PRD is too long / too vague", "tighten this spec for an engineer or agent", "what's the bet", "what problem are we solving", "acceptance criteria", "success criteria", "kill / scale / graduate thresholds", "measurement plan", or when scoping a feature's problem, bet, success behaviors, and evaluation before any behavioral spec. Part of the spec-dd workflow; precedes /spec-dd:spec.

This skill should be used when the user asks to "write specifications", "create test specifications", "specification-driven development", "spec-first", "behavioral specs", "derive test scenarios", "test implementation specification", "check specification alignment", "review specs", "verify implementation", or "spec-dd". Also triggers when the user mentions "SDD", "SDD-TDD", "spec-driven", "behavioral testing workflow", "test-first design", or asks about writing specifications before code, deriving tests from specs, or verifying implementation against specifications. Supports a full workflow walkthrough or focusing on individual phases.

Generate arc42 architecture documentation from a codebase. Read the repository into a structured evidence base, then author the 12 arc42 sections — emitting Mermaid diagrams where the code gives high-confidence structure, and explicit typed GAP flags where human input is needed, never fabricating. Use when asked to create, scaffold, or update arc42 docs, an architecture document, or per-section architecture views (building block view, runtime view, deployment view, etc.) for a project.

Selects the best-matching Kamino agent template for a given task, fills its template variables from the provided task and context, verifies no placeholders remain, and writes the completed agent file into the per-task folder .kamino/tasks/<task_id>/. Use when the user provides a task and wants a Kamino agent chosen and instantiated, mentions selecting or creating an agent from .kamino/agents, references the kamino agent index, or asks to run template-replace on an agent template.

Executes an assembled pipeline of instantiated Kamino agents in sequence using subagents, verifying each agent's output before proceeding to the next. Reads the run order from a dispatch-queue's execution-graph.md, prints the sequence to the terminal, and runs each step. Use when the user has a dispatch-queue (from taskgraph) or instantiated agent files and wants them executed, or asks to run/execute the assembled agents and confirm each step worked.

Copies this Kamino factory into a new folder in virgin state by running copy-factory.sh — installing both the .claude/ control plane (afac plugin manifest, skills, judge and classifier agents) and the .kamino/ data plane (blueprints, deterministic scripts, eval schemas), with an empty ledger and no inherited run data. Use when the user wants to install, clone, bootstrap, or set up a fresh agent factory in another repository or directory, asks to copy the factory somewhere, or invokes /copy-factory.

Deterministic read-only search over completed task outcome ledger records to produce score-free Agent Factory candidates.

Validates the Kamino agent library by running template-variable-checks.sh over the .kamino/agents directory — confirming every agent's required_inputs match the {{variables}} used in its body (both directions) and that its hardcoded_properties declaration is present and accurate. Use when the user wants to check or validate the agents, verify template-variable consistency, lint the agent blueprints, or invokes /check.

Ingests a source of problems + solutions from disk (a crawl, a dataset, a folder of problem files) into a standard-shape evaluation corpus the factory can sweep. Because the factory engine stays 100% corpus-agnostic, this skill does NOT hardcode any source format — it interviews the user, AUTHORS a corpus-specific builder script on demand, snapshots the ground-truth answers, runs the builder, validates the result against the corpus integrity gates, and records provenance. The authored builder and its input data live with the ingestion record (git-tracked), never in the generic engine. Use when the user wants to turn a problem set / dataset / answer list into a corpus, add a new corpus, ingest LeetCode/Project-Euler-style problems, or "make a corpus out of this folder".

Creates a new reusable Kamino agent blueprint (an agent template) from the blueprint scaffold. It discovers the authoring fields marked with <<...>> in the scaffold, interviews the user for each (persona, model, effort, rules, definition of done, steps, output format, input schema), fills them in, leaves the {{...}} invocation variables intact, writes the blueprint into the ad-hoc tier, and registers it in the index. Use when the user wants to add a new agent type, create an agent blueprint or template, design a new agent from scratch, or extend the .kamino/agents library so clone can later select it.

Benchmarks one prescribed agent blueprint against a task corpus — the caller pins the agent, and every corpus task is solved by that same agent, never the factory's own picking. This measures one agent's quality, not the factory's routing. Requires a corpus directory and an agent blueprint path as input. Per attempt it compiles an isolated run (the solver sees only the problem statement; all test tiers stay outside its reach), dispatches the solving subagent, judges success deterministically, appends the ledger, and finally regenerates the HTML report pages. Use when the user wants to evaluate, benchmark, or test a specific agent blueprint against a corpus, or run an agent-vs-corpus sweep.

Map a goal to a chain of atomic memento skills using the skill graph (Dijkstra), or flag exactly which atomic skill is missing when no chain exists. Use when the user states a goal to accomplish with memento skills (e.g. "download video [url] and extract the transcript"), asks how to get from A to B with skills, or asks which skill is missing.

Add a new atomic skill to the .memento library and rebuild the skill graph. Use when the user asks to add or create a memento skill (e.g. "add a memento skill for extracting video frames"), or when /memento reported a MISSING SKILL that should now be created.

Rebuild the memento skill graph from all SKILL.md files. Use when the user asks to rebuild or refresh the skill graph, after any manual edit under .memento/skills/, or when tools report the graph files are out of sync.

Remove an atomic skill from the .memento library and rebuild the skill graph. Use when the user asks to remove or delete a memento skill (e.g. "remove the kokoro tts skill").

Update an existing atomic skill in the .memento library (interface types, procedure, helper scripts, or rename/move) and rebuild the skill graph. Use when the user asks to change, edit, rename, or move a memento skill.