multi-agent-orchestration skillA
multi-agent-orchestration is agent-read markdown (skill) from jnpiyush/agentx: Design and operate multi-agent systems where several specialized LLM agents collaborate. Use when choosing between supervisor/worker, swarm/handoff, hierarchical, or graph patterns; selecting frameworks (AutoGen, CrewAI, OpenAI Swarm/Agents SDK, LangGraph, Microsoft Agent Framework, Google A2A); designing handoff contracts; preventing infinite loops, role drift, and coordination failures..
Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.
What the file says
# Multi-Agent Orchestration > **Purpose**: Coordinate multiple specialized agents to solve tasks no single agent can handle reliably. > **Scope**: Topologies, handoff protocols, framework selection, failure modes, anti-patterns. --- ## When to Use This Skill - Task spans multiple specialties (research + code + review) and a single agent loop loses focus - Need explicit role separation for auditability or compliance - Long-horizon tasks where one agent's context budget is insufficient - Cross-organization agent communication (A2A protocol) ## When NOT to Use Multi-Agent - Single-domain task -- a well-prompted single agent is cheaper and more reliable - Latency-sensitive (<1s) -- handoffs add round-trips - Tasks solvable by tool calls alone -- prefer tool-use-and-function-calling --- ## Topology Decision Tree ``` What is the task structure? +- Linear pipeline (research -> draft -> review)? | -> Sequential / Pipeline +- One coordinator delegates to specialists? | -> Supervisor / Worker (most common) +- Peers swap control based on context? | -> Swarm / Handoff (OpenAI Swarm pattern) +- Tree of sub-tasks? | -> Hierarchical (manager -> sub-managers -> workers) …
Read the whole file at its exact version.
How to install
mdr add jnpiyush/agentx/multi-agent-orchestration@v1.0.0mdr add jnpiyush/agentx/multi-agent-orchestration@sha256:9413964454508153Pin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.
[](https://markdownregistry.com/a/art_34bruunqqjzs2slc)
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Versions
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| v1.0.0 latest | 2026-09-15 | f17c505 | 6,062 B | A | view · diff |
| v1.0.0 | 2026-04-30 | 4f38ce8 | 6,060 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (6062 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
jnpiyush/agentx · 16 stars · license Apache-2.0 · pushed 2026-09-21 · branch master
API
GET https://markdownregistry.com/api/v1/artifacts/art_34bruunqqjzs2slc GET https://markdownregistry.com/api/v1/resolve?ref=jnpiyush/agentx/multi-agent-orchestration GET https://markdownregistry.com/api/v1/blob/941396445450815354467e266de6d4f845c7933cfafbde4a90a0392b3cc9e07d
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