cm-autopilot
Easy-to-use conversational CLI (Claude Code style) for non-technical users to spawn parallel AI tasks supervised by a visual web dashboard.
Skill Chain Engine — compose skills into automated pipelines. One task triggers multi-skill workflows with progress tracking, auto-detection, and step management.
$ npx -y skills add tody-agent/codymaster --skill cm-skill-chain --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/cm-skill-chainContext preview
The summary Claude sees to decide when to auto-load this skill.
Skill Chain Engine — compose skills into automated pipelines. One task triggers multi-skill workflows with progress tracking, auto-detection, and step management.
name: cm-skill-chain description: Skill Chain Engine — compose skills into automated pipelines. One task triggers multi-skill workflows with progress tracking, auto-detection, and step management.
> **TRIZ #40 Composite Materials** — Skills compose into pipelines. > One command → full workflow → automated step progression.
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"
| 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 |
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.
`brainstorm-idea* → planning → tdd → execution → quality-gate → safe-deploy*` *optional steps — only activated when task context scores them relevant
`debugging → tdd → quality-gate`
`content-factory → ads-tracker → cm-cro-methodology`
`project-bootstrap → planning → tdd → execution → quality-gate → safe-deploy*` *optional steps selected by task relevance
`cm-code-review → quality-gate → safe-deploy`
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):**
If a chain has more than 3 mandatory steps, all mandatory steps run and a performance advisory is logged.
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
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:**
**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/...
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
"I can't write code. But in 6 months, I shipped 12 real products using AI. CodyMaster is everything I learned — so you don't have to repeat my mistakes." — Tody Le, Head of Product, Creator of CodyMaster 50+ skills. One install.
Repo: tody-agent/codymaster
Easy-to-use conversational CLI (Claude Code style) for non-technical users to spawn parallel AI tasks supervised by a visual web dashboard.
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