accelerate
Use when the workflow is too slow, too expensive, or both and needs latency, cost, or token…
Use when the workflow needs multi-step processing with sequential, parallel, or conditional tool compositions and proper data flow.
$ npx -y skills add sharpdeveye/maestro --skill chain --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/chainContext preview
The summary Claude sees to decide when to auto-load this skill.
Use when the workflow needs multi-step processing with sequential, parallel, or conditional tool compositions and proper data flow.
name: chain description: "Use when the workflow needs multi-step processing with sequential, parallel, or conditional tool compositions and proper data flow." argument-hint: "[pipeline description]" category: enhancement version: 2.0.0 user-invocable: true
Invoke /agent-workflow — it contains workflow principles, anti-patterns, and the **Context Gathering Protocol**. Follow the protocol before proceeding — if no workflow context exists yet, you MUST run /teach-maestro first. Consult the tool-orchestration reference in the agent-workflow skill for composition patterns and error handling.
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Design tool chains that do complex work reliably. A chain is only as strong as its weakest link.
**Sequential**: A → B → C (each step depends on the previous) **Parallel**: [A, B, C] → Merge (independent steps run simultaneously) **Conditional**: A → (if X then B, else C) → D (branching based on results) **Iterative**: A → Check → (if not done) → A again (loop until convergence)
For each chain, define:
## Chain: [Name] ### Steps 1. [Tool A] — [what it does] — Input: [schema] — Output: [schema] 2. [Tool B] — [what it does] — Input: [output of step 1] — Output: [schema] 3. [Tool C] — [what it does] — Input: [output of step 2] — Output: [schema] ### Data Flow Step 1 output.field_a → Step 2 input.source_data Step 2 output.results → Step 3 input.items ### Error Handling Step 1 failure → [retry 3x, then return error] Step 2 failure → [return partial results from step 1] Step 3 failure → [retry with simplified input] ### Constraints Max total execution time: 60s Max retries per step: 3
After building the chain, run `/fortify` to add error handling at each step, then `/evaluate` to test the full pipeline.
**NEVER**:
Workflow fluency for AI coding agents. 1 core skill · 25 commands · 7 domain references · memory layer · audit trail — works across Cursor, Claude Code, Gemini CLI, Copilot, and 6 more.
Repo: sharpdeveye/maestro
Use when the workflow is too slow, too expensive, or both and needs latency, cost, or token…
Use when porting a workflow to a different AI provider, deployment environment, model tier,…
Use when any Maestro command is invoked — provides foundational workflow design principles…
Use when the workflow works but needs to handle more complex cases or produce higher-quality…
Use when workflow components are inconsistent, naming conventions vary, or a new team…
Capture a session summary — what was done, what decisions were made, and what to do next.