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vCFD

vCFD

by gpu7
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

get_logs

Fetch the tail of a CFD solver or mesh job log, with residual-friendly filtering, to monitor convergence and job status.

Instructions

Return the tail of a solver/mesh job log (filtered residual-friendly).

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_logs"
  }
}

Input Schema

NameRequiredDescriptionDefault
linesNo
job_idYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.6/5.0
Behavior2/5

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

No annotations are provided, so the description must disclose behavior. It states the output is a tail and 'filtered residual-friendly', but does not mention whether the operation is read-only, if the job must exist, or what happens for empty logs. This is insufficient for a tool with no annotation safety profile.

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 description is one sentence with no extraneous words, stating the action and resource directly. Though 'filtered residual-friendly' is somewhat jargon-like, it is appropriately short and front-loaded.

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

Completeness2/5

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

Given the simple tool (2 parameters, output schema exists), the description is not complete. It lacks usage context and parameter semantics, making it hard for an agent to know when to call it and what lines does. The output schema may cover return values, but the missing guidance on job_id and lines is critical.

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

Parameters1/5

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

The schema has job_id (required) and lines (default 40), but the description does not explain either. 'Tail' implies lines, but it is not explicit. With 0% schema description coverage, the description should clarify parameter semantics; it does not.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb 'Return' and resource 'tail of a solver/mesh job log', clearly indicating it retrieves log output. It distinguishes from siblings like get_job_status by focusing on logs, but the ambiguous phrase 'filtered residual-friendly' prevents a 5.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives like get_job_status or summarize_results. The description does not mention any exclusions or preferred contexts.

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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