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Agent skill

Chain

by sharpdeveye in sharpdeveye/maestro

A skill your agent uses when the workflow needs multi-step processing with sequential, parallel, or conditional tool compositions and proper data flow.

MITAuto-check passed

Install Chain

skills CLI
$ npx skills add sharpdeveye/maestro --skill chain -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install sharpdeveye/maestro chain --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/sharpdeveye/maestro.git skills-src && mkdir -p .claude/skills && cp -r skills-src/source/skills/chain .claude/skills/chain && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
chain
GitHub stars
592
Token cost
~607 tokens
SKILL.md length
225 words
Files
1
Skills in repo
25
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when the workflow needs multi-step processing with sequential, parallel, or conditional tool compositions and proper data flow.

  • The workflow needs multi-step processing with sequential
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Conditional tool compositions and proper data flow

What it does

Chain is an agent skill from sharpdeveye/maestro. Use when the workflow needs multi-step processing with sequential, parallel, or conditional tool compositions and proper data flow.

Its SKILL.md is about 610 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: 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… The licence is MIT.

When your agent uses it

  • The workflow needs multi-step processing with sequential
  • Conditional tool compositions and proper data flow

Example prompts

  • “/chain”

What it can do on your machine

Read from SKILL.md and the folder at commit 00f9115. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Chain loads about 607 tokens when it runs. Until then it costs about 34 tokens; SKILL.md has 225 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~34
When it runs · the whole SKILL.md, loaded when a task matches
~607

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from sharpdeveye/maestro at commit 00f9115, republished under its MIT licence (© sharpdeveye). 225 words, ~607 tokens.

Download SKILL.mdSave it as .claude/skills/chain/SKILL.md (or your agent's skills folder).
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

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?)

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

© sharpdeveye, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in source/skills/chain of sharpdeveye/maestro.

Open the folder on GitHubat commit 00f9115

Compare with similar skills

Chain next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Chain compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Chain this skillsharpdeveye/maestro592—~607Automated safety check: PassMIT
Parallel Processingbenchflow-ai/skillsbench1.8k—~511Automated safety check: PassApache-2.0
Parallels Discord Roundtripopenclaw/openclaw392k—~788Automated safety check: PassMIT
Openclaw Parallels Smokeopenclaw/openclaw392k—~8.4kAutomated safety check: NotesMIT
Sbom Supply Chainsickn33/agentic-awesome-skills47k2 repos~3.4kAutomated safety check: PassMIT
Agent Supply Chaingithub/awesome-copilot40k1 repos~2.7kAutomated safety check: PassMIT

Similar skills

  • Parallel Processing

    benchflow-ai/skillsbench

    Parallel processing with joblib for grid search and batch computations.

    1.8k GitHub stars~511 tokensUpdated 2 mo ago
    Auto-check passed

  • Parallels Discord Roundtrip

    openclaw/openclaw

    Run macOS Parallels smoke with Discord send, host verification, host reply, and guest readback proof.

    392k GitHub stars~788 tokensUpdated today
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  • Openclaw Parallels Smoke

    openclaw/openclaw

    Prepare, snapshot, run, rerun, debug, or interpret OpenClaw Parallels guest install, onboarding, gateway smoke, and upgrade checks across macOS, Windows, and Linux.

    392k GitHub stars~8.4k tokensUpdated today
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  • Sbom Supply Chain

    sickn33/agentic-awesome-skills

    Generate, sign, and verify SBOMs and provenance attestations to secure the software supply chain.

    47k GitHub starsUsed in 2 repos~3.4k tokens
    SecurityAuto-check passed

  • Agent Supply Chain

    github/awesome-copilot

    Official

    Verify supply chain integrity for AI agent plugins, tools, and dependencies.

    40k GitHub starsUsed in 1 repo~2.7k tokens
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  • Supply Chain Security

    zhaoxuya520/reverse-skill

    A skill your agent uses for software supply-chain security assessment covering SBOM, SCA, CI/CD pipelines, container images, build integrity, dependency provenance, and vulnerability reachability.

    40k GitHub starsUsed in 4 repos~953 tokens
    SecurityAuto-check: warnings

More from sharpdeveye/maestro

All 25 skills in this repo

  • Accelerate

    sharpdeveye/maestro

    A skill your agent uses when the workflow is too slow, too expensive, or both and needs latency, cost, or token usage optimization.

    592 GitHub stars~745 tokensUpdated 5 mo ago
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  • Compose

    sharpdeveye/maestro

    A skill your agent uses when a single agent demonstrably cannot handle the task and multi-agent coordination is justified.

    592 GitHub stars~720 tokensUpdated 5 mo ago
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  • Diagnose

    sharpdeveye/maestro

    A skill your agent uses when the user wants to find problems, audit workflow quality, or get a comprehensive health check on their AI workflow.

    592 GitHub stars~1.5k tokensUpdated 5 mo ago
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  • Extract Pattern

    sharpdeveye/maestro

    A skill your agent uses when the user wants to create templates, extract reusable patterns, document solutions, or build a pattern library from working workflows.

    592 GitHub stars~664 tokensUpdated 5 mo ago
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  • Fortify

    sharpdeveye/maestro

    A skill your agent uses when the workflow lacks error handling, has been failing in production, or needs retry logic, fallback strategies, and circuit breakers.

    592 GitHub stars~688 tokensUpdated 5 mo ago
    Auto-check passed

  • Guard

    sharpdeveye/maestro

    A skill your agent uses when deploying to production, handling sensitive data, or the workflow needs safety constraints, input validation, and security boundaries.

    592 GitHub stars~783 tokensUpdated 5 mo ago
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Questions about Chain

What does Chain do?

A skill your agent uses when the workflow needs multi-step processing with sequential, parallel, or conditional tool compositions and proper data flow. Chain is an agent skill from sharpdeveye/maestro. Use when the workflow needs multi-step processing with sequential, parallel, or conditional tool compositions and proper data flow.

When should I use Chain?

Chain fits situations like: the workflow needs multi-step processing with sequential; conditional tool compositions and proper data flow.

How do I install Chain in Claude Code?

Run `npx skills add sharpdeveye/maestro --skill chain -a claude-code`. Or copy the skill folder (source/skills/chain in sharpdeveye/maestro) into .claude/skills/chain in your project. Claude Code loads it when a task matches its description.

How do I install Chain in Codex?

Run `npx skills add sharpdeveye/maestro --skill chain -a codex`. Or copy the skill folder (source/skills/chain in sharpdeveye/maestro) into .agents/skills/chain in your project. Codex loads it when a task matches its description.

Can I use Chain in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add sharpdeveye/maestro --skill chain -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/chain, .gemini/skills/chain, .github/skills/chain and .opencode/skills/chain in your project.

What does Chain need to run?

SKILL.md names no scripts, command-line tools or credentials: Chain is instructions for the agent only.

Does Chain access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Chain safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Chain use?

Chain is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Chain use?

About 607 tokens (SKILL.md is roughly 2.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Chain?

Skills that share tags, products or a category with Chain: Parallel Processing (benchflow-ai/skillsbench, 1.8k stars), Parallels Discord Roundtrip (openclaw/openclaw, 392k stars), Openclaw Parallels Smoke (openclaw/openclaw, 392k stars) and Sbom Supply Chain (sickn33/agentic-awesome-skills, 47k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Chain?

sharpdeveye (a GitHub user) maintains it in sharpdeveye/maestro, which has 592 GitHub stars. The repository holds 25 skills in this directory. The repository was last updated on April 29, 2026.

Source: sharpdeveye/maestro on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.