Skill Chain Engine

TRIZ #40 Composite Materials — Skills compose into pipelines. One command → full workflow → automated step progression.

When to Use

ALWAYS trigger for: chain, pipeline, workflow, multi-step, end-to-end, "run the whole thing", "full process", "feature pipeline", "bug fix flow", "from scratch to deploy", "brainstorm to ship", "skill chain", "full pipeline"

Quick Reference

Command	Description
cody chain list	Show all available chains
cody chain info <id>	Show chain pipeline details
cody chain auto "task"	Auto-detect best chain & start
cody chain start <id> "task"	Start specific chain
cody chain status [exec-id]	Show progress
cody chain advance <exec-id>	Complete current step, move to next
cody chain skip <exec-id>	Skip current step
cody chain abort <exec-id>	Cancel chain
cody chain history	View past chain runs

Naming Convention

Step names use short-form identifiers — the cm- prefix is stripped by convention. Full skill names: cm-brainstorm-idea, cm-planning, cm-tdd, cm-execution, cm-quality-gate, cm-safe-deploy, cm-debugging, cm-content-factory, cm-ads-tracker, cm-project-bootstrap, cm-code-review. All skills now use the cm- prefix convention.

Built-in Chains

🚀 feature-development (up to 3 active steps)

brainstorm-idea* → planning → tdd → execution → quality-gate → safe-deploy* *optional steps — only activated when task context scores them relevant

🐛 bug-fix (3 steps)

debugging → tdd → quality-gate

📝 content-launch (3 steps)

content-factory → ads-tracker → cm-cro-methodology

🏗️ new-project (up to 3 active steps)

project-bootstrap → planning → tdd → execution → quality-gate → safe-deploy* *optional steps selected by task relevance

🔍 cm-code-review (3 steps)

cm-code-review → quality-gate → safe-deploy

Intelligent Skill Selection (v5.1)

Chains no longer execute every step blindly. selectTopSkills() dynamically selects the top 3 most relevant steps for each task:

Task: "fix login timeout bug"
  → Scores each step by keyword overlap with task description
  → Mandatory steps (condition='always', optional=false) always included first
  → Optional steps ranked by relevance score, capped at 3 total
  → Result: debugging (score 105) → tdd (score 101) → quality-gate (score 100)

Why it matters (SkillsBench research):

• 2-3 focused skills → +18.6pp task performance
• 4+ skills → +5.9pp
• Monolithic loading → -2.9pp

If a chain has more than 3 mandatory steps, all mandatory steps run and a performance advisory is logged.

Workflow

1. Start: Use chain auto for auto-detection or chain start for specific chains
2. Execute: Work through each skill step, using @[/skill-name] to invoke
3. Advance: When step is done, run chain advance <id> "summary"
4. Repeat: Continue until all steps complete
5. Track: Use chain status to monitor progress anytime

Integration with Other Skills

• cm-continuity: Chain progress persists across sessions via CONTINUITY.md working memory
• cm-execution: Each chain step delegates to cm-execution for actual implementation
• cm-quality-gate: Automatically runs at end of each development chain
• Context Bus (v5): Every chain automatically maintains .cm/context-bus.json — shared state across all steps

Context Bus — Inter-Skill Coordination (v5)

When chain start runs, the context bus is initialized automatically:

chain start feature-development "add payment flow"
→ Creates .cm/context-bus.json with:
    pipeline: "feature-development"
    session_id: "<uuid>"
    current_step: "brainstorm-idea"
    shared_context: {}
    resource_state: { skeleton_generated: null, learnings_indexed: null, ... }

When chain advance runs after each skill completes:

chain advance <exec-id> "summary of what was done"
→ Updates context-bus.json:
    current_step: "planning"   ← moved forward
    shared_context.brainstorm-idea: { summary, affected_files, output_path }

What downstream skills gain:

• cm-planning can read brainstorm output path → no re-read of full filesystem
• cm-tdd can see which files planning created → targeted test generation
• cm-quality-gate knows exactly which files changed → focused review

Reading the bus:

cm continuity bus          # terminal pretty-print
cm_bus_read                # MCP tool (Claude Desktop)
cm://pipeline/current      # URI resolver (in skill prompts)

Publishing to the bus (inside a skill):

cm_bus_write skill=cm-planning summary="tasks.md created" output_path=openspec/...

For AI Agents

When dispatching tasks that match a chain pattern:

1. Check if task matches a chain: suggestChain(taskTitle)
2. If match found, suggest to user: "This task matches the X chain pipeline"
3. If user agrees, start the chain and invoke skills in order
4. At the START of each skill step:
   → Read cm://pipeline/current to see upstream skill outputs
   → Check shared_context to avoid re-doing work
5. After completing each skill, advance the chain:
   → chain advance <id> "summary"
   → This updates context bus + CONTINUITY.md simultaneously