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run_all

Destructive

Broadcast one prompt to all enabled agents in parallel and receive each agent's answer labelled by agent, for comparing outputs or cross-checking a result.

Instructions

Fan the SAME prompt out to every enabled agent concurrently and return each agent's answer, labelled per agent — for comparing agents or cross-checking a result. Spawns every CLI (each can read/edit files in cwd) so it can be slow or use several agents' quotas; one confirmation covers the whole batch.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cwdNoWorking directory for every CLI. Prefer an absolute path; a relative path resolves from the server process's cwd. Not a sandbox.
modelNoOptional model id applied to EVERY agent as a fallback. Model namespaces do not overlap between agents, so a single value is usually valid for only one of them — prefer `models` for a fan-out. Must match [A-Za-z0-9][A-Za-z0-9._:/-]{0,127} — a flag-shaped value is rejected.
modelsNoPer-agent model overrides, e.g. {"codex":"o3","agy":"gemini-3.6-flash-low"}. Takes precedence over `model` for the agents named; any agent not listed falls back to `model`, then to its own CLI default. Keys must be enabled agent names (an unknown name is rejected with the valid list). Each value must match [A-Za-z0-9][A-Za-z0-9._:/-]{0,127}.
promptYesThe task or question to send to every agent, in natural language.
timeoutMsNoPer-agent TOTAL runtime cap in milliseconds once each CLI starts (process group killed if exceeded; default 1800000 = 30 minutes).
idleTimeoutMsNoPer-agent idle/inactivity timeout in milliseconds — killed only if the agent produces NO output for this long (resets on each output chunk; default 300000 = 5 minutes).
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate destructive/open-world behavior, and the description supplements this with concrete details: 'each can read/edit files in cwd' and 'one confirmation covers the whole batch.' It also mentions performance and quota impacts. This adds value beyond the provided annotations without contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the primary action, followed by a purpose clause and a caveat-rich second sentence. Every phrase earns its place with no redundancy or fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the core purpose, return format, file access, confirmation behavior, and performance implications. Given the rich schema and annotations, this is a solid overview. It does not mention every detail (e.g., model fallback rules or timeout mechanics), but those are fully documented in the schema, so the description is sufficiently complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, and each parameter already has a detailed description (e.g., cwd is 'not a sandbox', model formatting rules, timeout semantics). The tool description only references cwd behaviorally but doesn't add new meaning beyond the schema. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: 'Fan the SAME prompt out to every enabled agent concurrently and return each agent's answer, labelled per agent.' It uses a specific verb ('fan out') and resource ('every enabled agent'), and distinguishes this from sibling tools like codex/claude, which target a single agent.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives context on when to use the tool: 'for comparing agents or cross-checking a result.' It also warns about costs: 'can be slow or use several agents' quotas.' However, it does not explicitly name an alternative tool for single-agent use, so it falls just short of a perfect 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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