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Found 15 Skills
Exploratory Data Analysis skill for CSV and parquet datasets with deterministic profiling, drift/anomaly scans, contract generation and validation, and optional memory writeback into skill-system-memory. The implementation is Polars-first (lazy scan for large files and early `--sample` head), includes high-cardinality guards for profile/importance/contract flows, and supports categorical correlation with Cramer's V. Use when building or reviewing tabular fraud/risk/data-quality workflows, profiling new datasets, checking leakage or drift, or saving/validating data contracts.
Persistent shared memory for AI agents backed by PostgreSQL (fts + pg_trgm, optional pgvector). Includes compaction logging and maintenance scripts.
Agent behavioral profiles that standardize how different LLMs behave. Load this skill when you need to: (1) adopt a specific behavioral mode for a task, (2) switch between creative/strict/talkative modes, (3) ensure consistent behavior across different models. Profiles define personality, decision heuristics, communication style, and quality standards.
Canonical ticket lifecycle engine for multi-agent orchestration. Two backends: (1) filesystem YAML bundles for project-level work management (roadmap → bundle → tickets → review), (2) DB-backed durable tickets for session-level claim/block/close lifecycle. This skill is the single source of truth for all ticket operations.
Parent skill. Focuses on researching personal judgment, methodology, system capability and brand equity building in the AI era. Responsible for overall positioning control and task distribution.
기업교육 컨설턴트 리더를 위한 Claude Code 학습 튜터. "/cc-tutor", "/learn", "학습", "튜터" 요청에 사용.
Build and deploy autonomous AI agents with CowAgent - planning, memory, knowledge base, skills, and multi-channel support
Generate standalone interactive dashboard HTML from skill graph, TKT, memory, and roadmap data.
Working memory for thinking out loud.
Configurable gate validation skill. Use when running repository-local gate rules from gate_rules.yaml (command/structural/eda-contract), checking legacy experiment registry safety, or enforcing close-gate fail-closed validation.
BDD-style behavior specification engine for the skill system. Use when: (1) defining a new skill's behavior before implementation, (2) validating a spec against the schema, (3) generating a behavior contract (Mermaid DAG) from a spec, (4) running structural acceptance tests against a built skill. Workflow: Spec → Test → Develop → Contract.
Expert guide for working with opencode.ai - TUI commands, CLI operations, custom commands, agents, tools, skills system, and AGENTS.md configuration