chain-patterns

Solid

Chain patterns for CC 2.1.71 pipelines — MCP detection, handoff files, checkpoint-resume, worktree agents, CronCreate monitoring. Use when building multi-phase pipeline skills. Loaded via skills: field by pipeline skills (fix-issue, implement, brainstorm, verify). Not user-invocable.

AI & Automation 208 stars 20 forks Updated today MIT

Install

View on GitHub

Quality Score: 88/100

Stars 20%
77
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

# Chain Patterns ## Overview Foundation patterns for CC 2.1.71 pipeline skills. This skill is loaded via the `skills:` frontmatter field — it provides patterns that parent skills follow. ## Pattern 1: MCP Detection (ToolSearch Probe) Run BEFORE any MCP tool call. Probes are parallel and instant. ```python # FIRST thing in any pipeline skill — all in ONE message: ToolSearch(query="select:mcp__memory__search_nodes") ToolSearch(query="select:mcp__context7__resolve-library-id") ToolSearch(query="select:mcp__sequential-thinking__sequentialthinking") # Store results for all phases: Write(".claude/chain/capabilities.json", JSON.stringify({ "memory": true_or_false, "context7": true_or_false, "sequential": true_or_false, "timestamp": "ISO-8601" })) ``` **Usage in phases:** ```python # BEFORE any mcp__memory__ call: if capabilities.memory: mcp__memory__search_nodes(query="...") # else: skip gracefully, no error ``` Load details: `Read("${CLAUDE_SKILL_DIR}/references/mcp-detection.md")` ## Pattern 2: Handoff Files Write structured JSON after every major phase. Survives context compaction and rate limits. ```python Write(".claude/chain/NN-phase-name.json", JSON.stringify({ "phase": "rca", "skill": "fix-issue", "timestamp": "ISO-8601", "status": "completed", "outputs": { ... }, # phase-specific results "mcps_used": ["memory"], "next_phase": 5 })) ``` **Location:** `.claude/chain/` — numbered files for ordering, descriptive names for clarity....

Details

Author
yonatangross
Repository
yonatangross/orchestkit
Created
6 months ago
Last Updated
today
Language
TypeScript
License
MIT

Integrates with

Similar Skills

Semantically similar based on skill content — not just same category

AI & Automation Listed

chain

Execute a YAML-defined chain of skill invocations as a single reproducible, audited workflow — with template-driven input piping, schema validation, retry-on-malformed, conditional steps, gates (filesystem / semantic / tool), per-step worktree isolation, and JSONL audit logging. Use when the user says "run the X chain," "execute the X chain on Y," "chain these skills," "run this skill sequence," "run chain," "execute validate-<topic>," or names a chain defined in the workspace `chains/` or `drafts/sample-chains/` directories. Also offer this proactively when the active primary is about to manually run several skills in sequence on the same artifact, where the same sequence is likely to repeat — turning the ad-hoc flow into a chain YAML up-front buys reproducibility, audit trail, and consistent gate enforcement across runs.

0 Updated today
sumitake
AI & Automation Listed

corpus-chain

Traverse the pg-claude knowledge graph to answer "what does this feature/file/pattern touch across the corpus?" — pulls scenarios, idioms, call-site file examples, sibling patterns, subsystem ownership, and analogous past features from planning/ + sessions/ into a single chain map. Uses the graph edges built by `scripts/populate-idiom-callsites.py` (idiom → files) and `scripts/build-scenario-idiom-matrix.py` (scenario ↔ idiom bidirectional). Use proactively when brainstorming a new PG feature, planning §3 file table, investigating an unfamiliar subsystem, or trying to find "have we touched something like this before?". Also use inside `pg-feature-brainstorm` step 1 (subsystem framing) and `pg-feature-plan` before §3 to seed the file list from existing evidence rather than pure grep. Skip when you already have the anchor's downstream chain memorized, when the task is a one-file bug fix, or when the ask is about non-PG code.

0 Updated 5 days ago
matejformanek
AI & Automation Solid

skill-factory

Analyze session work and automatically convert reusable patterns into Claude Code skills. Use when: "세션을 스킬로", "스킬 만들어", "이거 스킬로", "skill factory", "이 작업 자동화해", "스킬 추출", "make this a skill", "extract skill", "convert to skill", "스킬 팩토리", "자동 스킬 생성". Differs from skill-creator (archived) and manage-skills (drift detection): this skill actively analyzes sessions, checks for duplicates, and creates skills via Agent Teams.

5 Updated yesterday
immacualate