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Nanites

Nanites

by ADn-001
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

Check Adaptation

check_adaptation

Checks a profile for divergence from nanites-default, prompting users to draft custom test units when the default plan may be poorly calibrated.

Instructions

Check whether a profile's use case diverges from nanites-default. When it does, returns a user prompt asking whether to draft custom test units, plus the default-plan notice that reusing the default plan may not be well-calibrated.

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>"
    },
    "name": "check_adaptation"
  }
}

Input Schema

NameRequiredDescriptionDefault
profileYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.6/5.0
Behavior4/5

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

With no annotations, the description carries the transparency burden. It clearly signals a read-only check and discloses the main behavioral outcome: a returned user prompt about drafting custom test units plus a default-plan notice. It does not explicitly rule out side effects or describe the negative-branch behavior, but 'Check whether' strongly implies inspection.

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 a single front-loaded sentence that states the core action immediately and then adds the conditional output. It is reasonably concise, though the phrase 'default-plan notice that reusing the default plan...' is slightly redundant and could be tightened.

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

Completeness3/5

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

The description covers the positive branch well: when divergence is detected, the agent should expect a user prompt and a notice. However, it does not describe what happens when the profile does not diverge, which matters because there is no output schema. It also leaves the exact meaning of 'nanites-default' and the required profile identifier format implicit.

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 schema provides only a string type and minLength for 'profile', with 0% description coverage. The description does add some semantic context by referring to 'a profile's use case,' but it still does not clarify whether the value should be a profile name, ID, or path. This is adequate but leaves a clear gap.

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 names a specific verb and resource: it checks whether a profile's use case diverges from nanites-default. It also states the conditional output, a user prompt about drafting custom test units plus a default-plan notice. This is specific enough to distinguish it from siblings like validate_test_unit or register_adapted_units.

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?

The description explains what the tool checks but gives no guidance on when to choose it over alternatives, nor any when-not-to-use conditions. Usage must be inferred from the tool's purpose, so there is no explicit routing or exclusion information.

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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