Is the org chart of agents earning its overhead — role clarity, orchestration fit, the communication tax, and what one agent with better tools would do instead.
Free & open · no signup · read-only — it ends by asking · nothing leaves your machine
You are working inside this repo. Mission: map how the agents are organized — who does what, who talks to whom, who decides — and judge whether the topology earns its coordination overhead.
Read-only pass. Your only write is the report file.
Phase 2 sweeps the codebase through every one of these, citing file and line for each finding.
can each agent's job be stated in one line that no sibling's line overlaps; overlap is where duplicated work and contradictions breed
the single-agent counterfactual: would one agent with these tools and a better prompt do the same job; what does the split actually buy
tokens spent describing work to other agents versus doing the work; count it on a real run
what context survives each hop; the summary that dropped the one constraint that mattered
one agent errs or stalls: who notices, what retries, and whether partial results poison downstream agents
two agents disagree: who rules, or does the loudest last message win; any deadlock or ping-pong paths
one request traceable across all agents with correlated ids, or N disconnected logs
the same documents and instructions billed through every agent's context window; measure the duplication
One structured report at the repo root — or in reports/, if you keep one — the same shape every time, ready for a teammate — or the optional Studio — to act on.
Every Goal Prompt follows the same four steps, so results are consistent and repeatable — no matter which one you run.
List every agent.
Role clarity — can each agent's job be stated in one line that no sibling's line overlaps.
Price a representative run.
Create TOPOLOGY.md at repo root.
Copy it and paste it into your agent inside the repo you want checked.
Install the goal plugin once — two commands — then just type /goal:multi-agent-topology.
/plugin marketplace add GhostlyGawd/goal-prompts/plugin install goal@goal-promptsOr install only this Goal Prompt as /goal-multi-agent-topology:
curl -fsSL https://goal-prompts.vercel.app/install | BRIEF=50 shLet an agent fetch it mid-conversation, or pull the raw Goal Prompt by URL.
https://goal-prompts.vercel.app/raw/50.mdNothing hidden — this is the whole Goal Prompt, verbatim. Read it in a minute, edit it, or copy it as-is.
# Goal: Multi-Agent Topology Review You are working inside this repo. Mission: map how the agents are organized — who does what, who talks to whom, who decides — and judge whether the topology earns its coordination overhead. Read-only pass. Your only write is the report file. ## Phase 1 — Map the organization - List every agent: role, model, system prompt, tools it holds, who spawns it, what it returns. - Draw the message paths: orchestrator to worker, peer to peer, shared memory, queues. Note what each hop serializes and re-explains. - Name the topology honestly: pipeline, supervisor/workers, router, swarm — or accidental. ## Phase 2 — Audit through 8 lenses 1. **Role clarity** — can each agent's job be stated in one line that no sibling's line overlaps; overlap is where duplicated work and contradictions breed 2. **Topology fit** — the single-agent counterfactual: would one agent with these tools and a better prompt do the same job; what does the split actually buy 3. **Communication tax** — tokens spent describing work to other agents versus doing the work; count it on a real run 4. **Handoff loss** — what context survives each hop; the summary that dropped the one constraint that mattered 5. **Failure propagation** — one agent errs or stalls: who notices, what retries, and whether partial results poison downstream agents 6. **Authority** — two agents disagree: who rules, or does the loudest last message win; any deadlock or ping-pong paths 7. **Observability** — one request traceable across all agents with correlated ids, or N disconnected logs 8. **Cost multiplication** — the same documents and instructions billed through every agent's context window; measure the duplication ## Phase 3 — Curate - Price a representative run: total tokens, the share spent on coordination, wall-clock lost to hops. - Write the counterfactual honestly: what a simpler topology would cost, and what it would lose. ## Phase 4 — Report Create `TOPOLOGY.md` at repo root: 1. **Org chart** — agent · role · model · tools · spawned by 2. **The coordination tax** — the arithmetic from a real run 3. **Findings** — ranked by cost × confusion 4. **Restructure options** — merge, split, or re-wire; each with what it saves and what it risks Start the report with today's date. If `TOPOLOGY.md` already exists from a previous run, read it first and lead with what changed since. ## Rules - More agents is a cost, not an achievement — the burden of proof is on the split - Judge from real traces where they exist, code paths where they don't - No multi-agent system in this repo? Say so in a one-paragraph null report and stop — a null result is a valid finding. - If a `reports/` directory exists at the repo root, write the report there instead of the root. - Before asking, present the top findings as a ranked list in plain words - Report only — end by asking which changes to make
reports/ directory exists at the repo root, write the report there instead of the root.Every system prompt in the repo: contradictions, dead instructions, bloat, and injection surface — with a consolidation plan.
Your tools are an API whose consumer is a model — audit names, descriptions, error contracts, and guards on destructive actions.
How runs end — iteration caps, stop conditions, stuck-state detection, and the true cost of one pathological run.
Reconstruct what actually enters the model's window each step — stale payloads, token hogs, retrieval junk, and buried instructions.