skill-agent-topology

Audit multi-agent workflows by counting coordination costs against boundary gains.

4.0k|375|Updated Jan 15, 2026
One-click install
npx skills add https://github.com/nyldn/claude-octopus --skill skill-agent-topology
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: skill-agent-topology
Source: https://github.com/nyldn/claude-octopus/tree/main/.claude/skills/skill-agent-topology
Command: npx skills add https://github.com/nyldn/claude-octopus --skill skill-agent-topology

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Multi-agent setups accumulate coordination overhead that often goes unmeasured, and teams keep adding agents without knowing whether each boundary earns its cost. This Skill audits an existing agent topology, counts what each handoff between agents costs, and compares it against what a single capable agent would have produced.

Core Features & Use Cases

  • Boundary Cost Analysis: Enumerates every context crossing between agents and names the specific cost at each one, including token burden, handoff loss, compression loss, semantic drift, verification burden, and governance overhead.
  • Gain Verification: Checks whether each boundary is earned by a gain a single agent could not produce, such as genuine specialisation, parallelism, cross-vendor diversity, or adversarial review.
  • Single-Expert Baseline Comparison: Compares the topology against the null hypothesis of one capable agent doing the whole task, placing the burden of proof on each boundary.
  • Use Case: A team running a five-agent review pipeline notices it is slow and agents keep agreeing. The audit reveals two agents whose inputs overlap heavily, recommends collapsing them into one, and identifies which artifact must carry context across the boundaries that remain.

Quick Start

Audit my current multi-agent workflow and tell me whether each agent boundary earns its coordination cost or should be collapsed.

Frequently Asked Questions about skill-agent-topology

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I audit whether my multi-agent setup is worth its cost?

List every point where context crosses from one agent to another, then name the cost and the gain at each crossing. Compare the result against what one capable agent would have produced; any boundary without a gain a single agent could not deliver is a candidate for removal.

When should I add another agent to an AI workflow?

Add an agent only when it provides a gain a single agent cannot produce: genuine specialisation, real parallelism, cross-vendor diversity from different training data, or adversarial review. Agreement between same-family models is not diversity and does not justify a boundary.

What is contextual transaction cost in multi-agent systems?

Contextual transaction cost is the overhead of making task context usable across an agent boundary, including token and latency burden, handoff loss, compression loss from summaries, semantic drift, verification work, and governance delays. The number of boundaries, not agents, drives this cost.

Can this audit a workflow that has not been run yet?

Yes, but the output must be flagged as a prediction rather than a measurement. An audit based on a real transcript or run directory counts observed crossings, while an audit of a described topology only reasons about intended ones.

When should I not use an agent topology audit?

Do not use it to pick a workflow for a new task, to decide whether to delegate to agents at all, to choose between providers or models, or for single-agent tasks where no boundaries exist. It also does not price safety, approval, or compliance boundaries.