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Nanites

by ADn-001
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

Share Test Results

share_test_results

Copy approved test results between profiles sharing the same LM Studio endpoint, avoiding redundant runs. Different endpoints are refused; later finalize aggregates the copied results without re-running.

Instructions

Copy approved test results from source_profile into profile when both point at the SAME LM Studio instance (endpoint fingerprint: normalized URL + auth presence). Opt-in sharing to avoid redundant regimen runs; different endpoints are refused and stay isolated. Nothing is auto-finalized — a later regimen/finalize aggregates the copied results without re-running the model.

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": {
      "profile": "<profile>",
      "source_profile": "<source_profile>"
    },
    "name": "share_test_results"
  }
}

Input Schema

NameRequiredDescriptionDefault
profileYes
model_idNo
source_profileYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.4/5.0
Behavior5/5

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

With no annotations, the description carries the full burden, and it delivers: it explains the endpoint fingerprint rule, refusal and isolation for different endpoints, the opt-in nature, and that nothing is auto-finalized. These are behavioral details beyond what the schema or annotations provide.

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 three sentences with no filler. The core action and destination are front-loaded, followed by the endpoint condition, then the non-finalization caveat. Every sentence adds necessary information.

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 tool with no annotations and no output schema, the description covers the main invocation constraints, behavior, and downstream effects well. The only notable gap is the unexplained optional model_id parameter, which prevents a perfect score.

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

Parameters3/5

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

The description explains the roles of source_profile and profile via the phrase 'from source_profile into profile.' However, schema description coverage is 0% and model_id is never mentioned, leaving its purpose and optional behavior undocumented. Some parameter meaning is added, but not complete.

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 states a specific operation — copying approved test results from source_profile into profile — and adds a defining condition (same LM Studio instance). This clearly differentiates it from sibling tools by resource and action, even without naming an alternative.

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?

It explicitly says when to use the tool: opt-in sharing to avoid redundant regimen runs. It also gives a when-not: different endpoints are refused and stay isolated. It mentions later regimen/finalize aggregation instead of naming a specific sibling alternative, so it is clear but not fully exhaustive.

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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