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Glama

get_role_config

Resolve the provider and model for each pipeline role from environment variables, model registry, and optional plan config to verify what a plan will run on before execution.

Instructions

Show the resolved (provider, model) for every pipeline role - overlord, planner, dispatch, review, decompose - given the current env vars and model_registry.json, optionally layered with a specific plan's role_config (pass plan_name to include it). Lets you check what a plan will actually run on before executing it. Pure read; makes no changes.

"planner" here reports its own explicit configuration layer (env var / plan role_config / registry) using the same "claude" bottom-of-chain default as the other roles - it does NOT reproduce the extra "mirror dispatch's own backend when nothing else is configured" fallback that _resolve_planner_backend applies at actual dispatch time (that fallback depends on a specific story's already-resolved dispatch backend, which doesn't exist outside of a real dispatch call).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
plan_nameNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.6/5.0
Behavior5/5

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

Since no annotations are provided, the description carries full behavioral burden. It explicitly states 'Pure read; makes no changes' and explains a non-obvious nuance about planner resolution (not reproducing the mirror fallback). This level of transparency about what the tool does and does not do is exemplary.

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

Conciseness4/5

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

The main purpose is front-loaded in the first sentence, and the second paragraph is a necessary caveat about planner behavior. While a bit verbose, every sentence adds value and there is no fluff. The structure is logical, though slightly longer than strictly needed.

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?

The description covers the tool's purpose, inputs, and a key behavioral caveat. An output schema exists, so return format does not need elaboration. For a complex config-resolution tool, the description gives an agent everything needed to call it correctly and interpret the result.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must compensate. It explains the only parameter (plan_name) by stating 'pass plan_name to include it', giving meaningful context beyond the bare schema. It does not detail format or constraints, but for a single optional string parameter, this is sufficient.

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 action (show resolved provider/model), the resource (all pipeline roles), and the inputs (env vars, model_registry.json, optional plan_name). It is specific and distinct from siblings like get_effective_config by enumerating the exact roles covered and the resolution layers.

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?

Provides a clear use case: 'check what a plan will actually run on *before* executing it'. This establishes when to use the tool, but it does not explicitly contrast with alternative config tools (e.g., get_effective_config) or state when not to use it. No exclusions are mentioned, so it falls short of a 5.

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