Explorar skills

Core technical documentation writing principles for voice, tone, structure, and LLM-friendly patterns. Use when writing or reviewing any documentation.

Detects common LLM coding agent artifacts in codebases. Identifies test quality issues, dead code, over-abstraction, and verbose LLM style patterns. Use when cleaning up AI-generated code or reviewing for agent-introduced cruft.

Interrupt controller converting polled to proactive agent execution. Per-runtime strategies, configurable thresholds, Deacon heartbeat supervision. Fights LLM passivity bias.

Process external code review feedback with technical rigor. Use when receiving feedback from another LLM, human reviewer, or CI tool. Verifies claims before implementing, tracks disposition.

Applies fixes from a prior review-llm-artifacts run, with safe/risky classification. Respects verify-llm-artifacts output when present to skip false positives.

Use when auditing an agent codebase against the 12-Factor Agents methodology, reviewing LLM-powered system architecture, or assessing agentic app compliance. Triggers on \"analyze agent architecture\", \"12-factor audit\", \"how compliant is this agent\", or \"evaluate this LLM app\". Also applies when comparing frameworks or planning agent improvements. Not for quick checklists \u2014 this perfor

Confirms or rejects findings from review-llm-artifacts before deletes or risky refactors. Loads review-verification-protocol-style checks per finding. Use after a review run, when the user wants to reduce false positives, before fix-llm-artifacts on dead code, or when validating a full-project scan.

Detects common LLM coding agent artifacts by spawning four parallel subagents over the project or changed files. Scans files changed since main by default; use --all for full-project scan. Triggers on LLM cruft cleanup, agent-generated code review, dead code sweeps, test-quality passes, or when the user asks to scan the whole repo.

Persist progress for long-running jobs (batched LLM calls, large ingestions, multi-hour syncs) so that a context reset, crash, or interrupt doesn't lose work. Use whenever a job iterates over N items and completing item K matters independently. Provides a resumable.mjs library pattern plus the skill's invocation heuristics.

Validates knowledge pack content against runtime schemas: .skillmeta against KnowledgePackSchema, modules against ModulesFileSchema, activities against PackActivitySchema. Checks cross-pack references, learning outcome uniqueness, and file completeness. Use when validating pack content after generation.

Persist progress for long-running jobs (batched LLM calls, large ingestions, multi-hour syncs) so that a context reset, crash, or interrupt doesn't lose work. Use whenever a job iterates over N items and completing item K matters independently. Provides a resumable.mjs library pattern plus the skill's invocation heuristics.

Generates knowledge pack content suites: vision documents, modules YAML, activities JSON, assessment frameworks, resource catalogs, and .skillmeta files. Shared by all 3 tier-specific author agents. Use when creating or updating pack content files.