chain
Use when the workflow needs multi-step processing with sequential, parallel, or conditional tool compositions and proper data flow.
What this skill does
## MANDATORY PREPARATION 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. --- Design tool chains that do complex work reliably. A chain is only as strong as its weakest link. ### Chain Patterns **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) ### Chain Design Process For each chain, define: ```markdown ## 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 ``` ### Chain Validation - [ ] Data schemas are compatible between connected steps - [ ] Every step has error handling - [ ] Total chain timeout is set - [ ] Maximum iteration count is set for loops - [ ] Partial results are handled (what if step 2 of 4 fails?) ### Recommended Next Step After building the chain, run `/fortify` to add error handling at each step, then `/evaluate` to test the full pipeline. **NEVER**: - Build chains without defining data contracts between steps - Create loops without maximum iteration counts - Skip error handling at any step (the chain breaks at the weakest link) - Assume output of step N is always valid input for step N+1 - Build long chains when a single prompt could handle the task
Related in enhancement
amplify
IncludedUse when the workflow works but needs to handle more complex cases or produce higher-quality output through better tools, context, prompts, or models.
enrich
IncludedUse when the agent needs access to information beyond its training data — knowledge sources, RAG pipelines, or grounding data.
guard
IncludedUse when deploying to production, handling sensitive data, or the workflow needs safety constraints, input validation, and security boundaries.
iterate
IncludedUse when the workflow needs to self-correct, improve over time, or establish feedback loops and evaluation cycles.
temper
IncludedUse when the workflow feels over-engineered, has premature optimizations, unnecessary abstraction layers, or complexity beyond actual requirements.
turbocharge
IncludedUse when the user wants to push past conventional workflow limits with advanced performance techniques like parallel orchestration, streaming pipelines, or adaptive routing.