chain
Use when the workflow needs multi-step processing with sequential, parallel, or conditional tool compositions and proper data flow.
pinned to #00f9115updated 2 weeks ago
Ask your AI client: “install skills/chain”.
Requires the metahub MCP server installed in your client. Set up MCP.
mh install skills/chainmetahub onboarded this repo on the author's behalf.
If you own github.com/sharpdeveye/maestro on GitHub, claim the listing to take over publishing. Your claim preserves the existing eval history and badges; only the curator label is replaced with verified-publisher on your next publish.
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402
Last commit
2 weeks ago
Latest release
published
- #agent-orchestration
- #ai
- #ai-agents
- #ai-workflows
- #claude-code
- #codex
- #copilot
- #cursor
- #developer-tools
- #gemini
- #open-source
- #prompt-engineering
- #skills
Evaluation report
WarningsAutomated checks the publisher passed at publish time — structure, docs, safety, and whether the artifact behaves as claimed.00f9115· 2 weeks ago
Kind-specific
31Skill: SKILL.md present
found at source/skills/chain/SKILL.md · frontmatter source: SKILL.md
Skill: body content present
372 words · 2,160 chars · 10 sections · 1 code block
Skill: triggers declaredwarn
No `trigger` phrases in SKILL.md frontmatter
Add `trigger:` lines so Claude knows when to activate this skill — e.g. `when building MCP servers` or `for diagram creation`.
Skill: allowed-tools scope
no allowed-tools restriction (Claude may use anything)
Release history
1- releasecurrent00f9115warn2 weeks ago
Contents
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:
## 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
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orchestration-patterns
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migration-patterns
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mh install skills/chain