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Muse bridge diagnostics

muse_status
Read-onlyIdempotent

Report diagnostics for the Muse Code bridge setup without spending quota. Checks bridge version, muse binary, credentials, cached model catalog, and Windows sandbox state.

Instructions

Report diagnostics for the Muse Code bridge setup (spends no quota).

Reports the bridge's own version and any newer release, then whether muse is found (and which binary the bridge runs), whether credentials are present (META_API_KEY or a muse login), any cached model catalog, the Windows OS sandbox state, and where muse keeps its data. Muse has no free auth probe, so a green auth row means credentials exist, not that they are still valid. This backend is EXPERIMENTAL: green here means the setup looks right, not that a real answer has ever been confirmed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.32.1

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already cover readOnly/idempotent/closed-world safety, yet the description still adds substantial behavioral context: what each diagnostic row means, the caveat that a green auth row only proves credentials exist (no live probe), and an EXPERIMENTAL warning that green does not mean a real answer was confirmed. This is exactly the extra context annotations cannot convey.

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 quota-free fact and the core purpose are front-loaded, and the enumerated diagnostics are information-dense rather than padding. It runs long across three blocks, but nearly every clause conveys a distinct fact (version, binary, credentials, catalog, sandbox, data location) that an agent would otherwise have to guess.

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 zero-param diagnostic tool with an output schema, the description is more than sufficient: it names what is checked, caveats the auth signal, and flags experimental status. Nothing an agent needs to decide whether and how to call it is missing.

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?

The tool takes zero parameters, so per the rubric this earns the baseline 4. The schema is fully empty and there is nothing the description could add about parameter meaning.

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?

States a specific verb and resource — 'Report diagnostics for the Muse Code bridge setup' — and immediately distinguishes itself from the ask/continue siblings by being a read-only diagnostic. An agent can identify this as the pre-flight check tool without opening the schema.

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?

'Spends no quota' gives a clear selection signal: this is the free way to check the bridge before invoking muse_ask. However, it never explicitly says when to prefer it over alternatives or what state it should be run in (e.g. before first use, after a failure).

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