Deliberation

panel

Read-only

Preview which AI providers would be dispatched for a given config and expert without calling them. Returns a JSON list of eligible providers for parallel execution.

Instructions

Return the names of the providers ask-all WOULD dispatch for the current config + expert (enabled built-ins + eligible OpenRouter aliases, fanout cap applied), WITHOUT calling them. Use this to discover the panel, then issue one ask-one call per provider in parallel for visible per-provider progress. Local and read-only (no provider calls); returns a text-wrapped JSON envelope { providers[], omitted[] }.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "panel"
  }
}

Input Schema

Name	Required	Description	Default
`cwd`	No	Working directory the provider runs in (used to resolve relative file refs). Defaults to the server process directory.
`expert`	No	Optional persona to preview the panel for; affects which providers/aliases are eligible.

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedv3.8.1Jun 18, 2026

addedInput schema / properties / cwd / description

Added value: +"Working directory the provider runs in (used to resolve relative file refs). Defaults to the server process directory."

addedInput schema / properties / expert / description

Added value: +"Optional persona to preview the panel for; affects which providers/aliases are eligible."

First observedv0.1.0Jun 17, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds value by confirming it is 'local and read-only (no provider calls)' and describing the return envelope, though annotations cover the safety profile well.

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, zero waste. First sentence delivers purpose and behavior, second gives usage guidance. Efficient and well-structured.

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

Completeness5/5

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

For a simple 2-param optional tool with rich annotations, the description covers purpose, behavior, return format, and usage flow. No gaps given the context.

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 description coverage is 100%, so baseline is 3. The description repeats the schema text for parameters without adding new meaning or syntax details beyond the schema.

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 it 'returns the names of the providers... WITHOUT calling them', distinguishing it from ask-all. It identifies the specific verb and resource (discover panel) and differentiates from siblings like ask-one.

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?

Explicitly states when to use: 'Use this to discover the panel, then issue one ask-one call per provider in parallel'. Provides clear context but lacks explicit exclusions or alternatives.

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