boinc-central-mcp

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batch_status

Read-onlyIdempotent

Retrieve the status of a single BOINC Central batch, including state, completion fraction, job counts, timing, and turnaround metrics.

Instructions

Status of one batch: state, fraction done, job counts (done, in_progress, unsent, failed), times and turnaround.

Turnaround: the RPC API gives no per-job sent/received times, so batch_turnaround_s is completion - submission for a finished batch (or elapsed time so far), and median_turnaround_s is the batch field the web page labels "Median turnaround time" (expire_time; usually unset for BUDA, then null). If the server reports per-job sent/received times, median_job_turnaround_s is their median. Set runtime_sample=N (<= 50) to also fetch N completed jobs and report the median elapsed and CPU run time of their canonical instances (one extra request per job).

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": {
      "batch_id": "<batch_id>"
    },
    "name": "batch_status"
  }
}

Input Schema

Name	Required	Description	Default
`batch_id`	Yes
`runtime_sample`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Oct 25, 2026

TDQS

A4.1/5.0

Behavior4/5

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

Annotations already cover safety (readOnly, idempotent, non-destructive), yet the description adds real behavioral context: how batch_turnaround_s and median_turnaround_s are derived, that median_turnaround_s is often null because expire_time is usually unset for BUDA, and that runtime_sample issues one extra request per job. That cost and nullability disclosure is well beyond the annotations, though it stops short of error behavior for a missing batch.

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 core purpose is front-loaded in one line, followed by a dense but purposeful paragraph on turnaround semantics and sampling cost. Every sentence carries information, though the turnaround explanation could be split more cleanly for scanning.

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?

For a two-parameter read-only status tool with an output schema, the description covers the truly ambiguous parts: the meaning of each turnaround field and the extra-request cost of runtime_sample. Missing only minor items such as behavior when batch_id does not exist.

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 carries the burden. It fully documents the non-obvious runtime_sample parameter (N <= 50, fetches that many completed jobs, one extra request per job, returns median elapsed and CPU run time of canonical instances), while batch_id is self-explanatory as an integer id.

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 opening sentence states a specific resource ('one batch') and enumerates exactly what is returned: state, fraction done, job counts, times and turnaround. The scope word 'one' implicitly contrasts it with the sibling list_batches, so an agent can pick between them without opening a schema.

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

Usage Guidelines3/5

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

Usage is implied by 'one batch' versus the plural siblings list_batches and batch_jobs, but the description never explicitly says when to choose this tool over batch_jobs for per-job detail or list_batches for enumeration. No exclusions or alternatives are stated.

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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