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claude-bridge

claude-bridge

by JosiahSiegel
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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get_dispatch

Poll a job's current state using its job ID. Returns status such as running, done, error, or abandoned.

Instructions

Non-blocking read of a job's current state.

status values:

  • running — work in flight; elapsed_ms included for progress.

  • done — full sync-style result keys.

  • cancelled — user called cancel_dispatch.

  • abandoned — runtime cancel (transport timeout, FastMCP shutdown). Subprocess kept running; watcher will transition this to done or error shortly. Poll again.

  • error — dispatcher-internal error or unparseable output.

  • orphaned — subprocess and output both lost on a restart.

Unknown job_id returns {ok: false, error: ...}. Works for both live jobs and ones loaded from disk after a bridge restart.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "job_id": "<job_id>"
    },
    "name": "get_dispatch"
  }
}

Input Schema

NameRequiredDescriptionDefault
job_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

No annotations exist, so the description must disclose behavior. It explains all possible statuses (running, done, cancelled, abandoned, error, orphaned), handling of unknown job_id, and that it works for live and disk-loaded jobs after restart. It does not mention authorization or rate limits, but it covers key behavioral traits.

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?

The description is concise: a single line for the main purpose followed by a bulleted list of statuses. No redundant information; every sentence adds value. Front-loads the key action.

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?

Given 1 parameter, no output schema, and no annotations, the description covers the tool's behavior comprehensively: status explanations, error handling for unknown IDs, and persistence across restarts. It is sufficient for an AI agent to understand what the tool does and what to expect.

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 only parameter job_id has 0% schema description coverage. The description adds meaning by specifying that an unknown job_id returns {ok: false, error: ...}, which is not in the schema. This compensates well for the lack of schema-level documentation.

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 starts with 'Non-blocking read of a job's current state,' which clearly specifies the action (read) and resource (job's current state). This distinguishes it from siblings like dispatch (create) and wait_dispatch (blocking wait).

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 phrase 'Non-blocking' implies when to use (avoid waiting) but does not explicitly contrast with alternatives like wait_dispatch. There are no when-not-to-use or exclusionary statements, though the context is reasonably clear.

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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