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Nanites

by ADn-001
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TypeScript
Hybrid

Register Adapted Units

register_adapted_units

Validate authored test units with Phase 4 validator and register those that pass; rejected units are returned with their validation issues, so nothing is silently dropped.

Instructions

Validate a batch of authored test units through the Phase 4 validator and register the ones that pass; each rejected unit is returned with its validation issues surfaced, never silently dropped or force-registered.

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>",
      "units": "<units>"
    },
    "name": "register_adapted_units"
  }
}

Input Schema

NameRequiredDescriptionDefault
unitsYes
profileYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.7/5.0
Behavior4/5

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

With no annotations provided, the description carries the full disclosure burden, and it delivers solid value: 'each rejected unit is returned with its validation issues surfaced, never silently dropped or force-registered' is a genuine behavioral commitment about failure handling that an agent would otherwise not know. It does not cover error behavior on partial registration failure or rate limits, but the core mutation semantics (validate-then-register) are well disclosed.

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?

A single dense sentence with the core action front-loaded before the behavioral guarantee. No wasted words, though the syntax is slightly run-on; every clause earns its place.

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 core flow (validate, register passing, return rejected with issues) well for a mutation tool. But it leaves the required `profile` parameter unexplained and gives no indication of return format beyond the rejected-units note. Moderate complexity with a loose `units` schema warrants a bit more, so this is adequate but not complete.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate for both parameters. It explains `units` as 'authored test units' in a batch, but the required `profile` parameter is never mentioned or explained — an agent cannot infer what profile means or how it affects registration. A 0% coverage schema with an unspecified required parameter is a significant 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?

States a specific verb+resource ('Validate ... test units ... register the ones that pass') with a concrete context (batch, Phase 4 validator). The batch scope clearly differentiates it from sibling singles like validate_test_unit and register_test_unit, so an agent can tell them apart without opening the 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?

The description implies this is the batch variant by saying 'a batch of ... test units', which hints at when to reach for it over the single-unit siblings. However, it never explicitly names the alternatives or states when NOT to use this tool, leaving the routing decision to inference.

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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