agent-orchestration
Skill0 starsChanged 35 days agoMITView on GitHub
Design, review, or simplify agent orchestration by deciding which work belongs in a shared agent loop, a tool, a skill, or a separate subagent. Use for delegation-boundary decisions, costly or lossy handoffs, and migrations that fold specialists into the main loop.
24 other projects use a version of this.
Adopted by
Most recently taken up by
- CassetteTapeCrackle/claude-starterstheir own version, first seen Nov 8, 2026
- juninmd/skillstheir own version, first seen Nov 8, 2026
- scoobydrew83/skillstheir own version, first seen Nov 3, 2026
- black-yt/skillstheir own version, first seen Nov 1, 2026
- Wiserax/wisecrafttheir own version, first seen Oct 25, 2026
- parcadei/Continuous-Claudetheir own version, first seen Oct 17, 2026
Used with
Projects with it also use mcp-builder and code-review.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
MicrosoftSkillmcp-builder
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
Also in 3 projects that use this
GoogleSkillcode-review
Adversarial systems, concurrency, memory-model, and architecture code review protocol. Use this skill whenever asked to review code, PRs, diffs, or branches in Filament.
Also in 3 projects that use this
Other versions24 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 24
- parcadei/Continuous-Claude★ 3.9ksame name
- parcadei/Continuous-Claude-v2★ 3.9ksame name
- parcadei/Continuous-Claude-v3★ 3.9ksame name
- codeaholicguy/ai-devkit★ 1.7ksame name
- GTMify/aigtm★ 25same name
- black-yt/skills★ 16same name
- Sathvikar01/Agent-engineering-skills★ 3same name
- juninmd/skills★ 2same name
- CassetteTapeCrackle/claude-starters★ 1same name
- hongdp/deskd★ 1same name
14 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository13 other files it gives its agents.
- advocatus-diaboliSkill
- agentic-harness-engineeringSkill
- agent-instruction-reliabilitySkill
- agent-instructionsSkill
- context-loadingSkill
- context-managementSkill
- copilot-usage-baselineSkill
- learning-loopSkill
- research-to-skillSkill
- skill-refinementSkill
- stateful-evidence-reasoningSkill
- technical-documentationSkill
- ticket-craftSkill
The file
We split this skill into the rules it gives an agent
2 rules. 0 are common, 2 are distinctive, and 0 are very specific to this project.
0
Common
Most of the 23 edited versions we read keep these.
2
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 37
When delegation is within the user's scope and the host permits it, give the worker the task, necessary inputs, constraints, allowed …
- Distinctive: line 49
Read evidence.md when the recommendation needs source appraisal, conflicting findings, or a refresh.
“Common” is measured: kept by at least 6 in 10 of the 23 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Agent Orchestration
Choose boundaries from context dependencies and task outcomes. A separate team, domain name, or reasoning phase is a candidate module, not sufficient reason for another agent.
Inspect the actual boundary
Establish the requested outcome and scope: architecture advice, an audit, or an implemented change. Inspect available prompts, tools, traces, and evaluations. For each candidate boundary, identify:
- Information needed on both sides, including user constraints, mutable state, exact identifiers, and earlier decisions.
- Work that can proceed independently, and whether its bulky intermediate material can be discarded.
- Evidence of repeated handbacks, missing information, duplicated investigation, tool-selection errors, or context-related failures.
- Effective tool access and enforcement, rather than permissions asserted only in a prompt.
Missing traces mean an architectural hypothesis, not a measured bottleneck. Do not invent usage frequencies or performance gains.
Choose the least costly adequate arrangement
| Observable condition | Candidate arrangement | What would change the choice |
| Phases repeatedly need the same evolving state or conversation | Keep reasoning in the main loop; load occasional procedures as skills | A separate context measurably helps despite the exchange cost |
| Existing specialists routinely operate together on the same evidence | Evaluate folding them into the main loop, or merging the coupled pair as an intermediate step | A necessary isolation boundary or a task regression |
| Work is a deterministic lookup, transformation, or API operation | Use a tool without an extra model loop | Adaptive investigation is actually required |
| Independent investigations produce much more intermediate material than the caller needs | Consider bounded workers with separate contexts and evidence-bearing results | Dependencies, duplication, or synthesis losses outweigh the benefit |
| A separate verifier can check an artifact against requirements without reconstructing its author's reasoning | Consider an independent check when its value justifies the cost | A superficial verdict adds no useful verification |
| Tool choice or instructions conflict in the shared loop | First clarify interfaces and defer irrelevant guidance; evaluate isolation if the conflict persists | Better discovery resolves the failure without another agent |
| A specialist genuinely needs to own an extended conversation with the user | Consider a full handoff with explicit state and ownership transfer | A bounded result is sufficient for the main agent to continue |
For new systems, one loop is a useful initial hypothesis when dependencies dominate. Parallel tool calls can handle independent operations without separate reasoning agents. For existing systems, retain the working baseline until a candidate is evaluated. Neither default establishes universal superiority.
Make a retained worker's boundary usable
When delegation is within the user's scope and the host permits it, give the worker the task, necessary inputs, constraints, allowed effects, completion condition, and expected result. Choose effort and concurrency from the task and available budget; this skill supplies no fixed agent count.
Require a usable result: status, findings or artifact location, supporting source/data identifiers, unresolved issues, and what was actually checked. Preserve exact values needed downstream. Inspect consequential evidence or artifacts before relying on a worker's conclusion; a summary can omit the decisive detail. Treat timeout or partial work as partial. If repeated clarification exposes hidden coupling, bring the dependent reasoning together or revise the boundary.
Separate contexts alone do not prove security isolation. Preserve actual restrictions when merging or folding; verify the host's effective permissions and tool behavior. An architecture review does not authorize spawning workers, changing live systems, or expanding access.
Change and verify
For migrations or comparisons of measured variants, read migration-and-evaluation.md. It covers obligation preservation, matched evaluations, regression handling, and rollback.
Deliver the proposed or implemented boundaries, their task-specific rationale, what the evidence establishes, and remaining uncertainty. Distinguish a plausible design, an executed test, and a demonstrated improvement.
Read evidence.md when the recommendation needs source appraisal, conflicting findings, or a refresh. For evaluating this skill, use requests.md; keep rubric.md out of a test worker's context.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

