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verify_intent

Re-run declared intent invariants after each edit as a regression gate. Returns pass/fail per invariant; inspects only and mutates nothing.

Instructions

Re-run every invariant declared with declare_intent — the regression gate to run after each edit. Composes check_shape / check_airtight_path / face-role resolution; never raises on a failing invariant (a failure is a passed=False row), so it is safe to call in a loop. Inspection only; mutates nothing.

handle: the part (must have a declared intent contract).

Returns a dict: handle (str) ok (bool) True iff every declared invariant passed results (list) one {invariant, passed, detail} per declared invariant — invariant in {watertight, airtight_path, required_faces}, detail a human-readable summary of what was measured

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
handleYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
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 does so well: it discloses that failures never raise (returned as passed=False rows), that it is safe in a loop, that it is inspection-only and mutates nothing, and that the handle must already have a declared intent contract. This is exactly the behavioral context an agent needs to invoke safely.

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?

Front-loads purpose, then behavior, then the parameter, then the return shape — a sensible progression with no filler sentences. The return block is verbose but justified since no output schema exists.

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

Completeness5/5

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

With no annotations, no output schema, and 0% schema description coverage, the description compensates fully: it specifies behavior, the input precondition, and the exact return structure (handle/ok/results with invariant enumerations). Nothing an agent needs to call it correctly is missing.

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 coverage is 0% and the schema itself says nothing about the single parameter, but the description supplies meaning and a precondition: 'handle: the part (must have a declared intent contract).' That materially clarifies the argument beyond the bare string type.

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 and resource — 're-run every invariant declared with declare_intent' — and frames it as 'the regression gate to run after each edit.' It also names what it composes (check_shape / check_airtight_path / face-role resolution), which lets an agent distinguish it from siblings like verify_feature or verify_contract.

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?

Gives clear usage context: run after each edit, and safe to call in a loop. It does not explicitly name alternatives (verify_feature, verify_contract) or when-not-to-use conditions, so it falls short of full routing guidance.

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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