world-model-mcp

get_constraints

Retrieve applicable linting, style, architecture, testing, or API contract rules for a file to ensure code compliance.

Instructions

Get constraints (linting rules, patterns, conventions) for a file

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": {
      "file_path": "<file_path>"
    },
    "name": "get_constraints"
  }
}

Input Schema

Name	Required	Description	Default
`file_path`	Yes
`constraint_types`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.7.3May 27, 2026

TDQS

A3.6/5.0

Behavior3/5

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

No annotations are provided, so the description carries the burden. It implies a read-only operation ('Get') but does not disclose potential behaviors such as error handling for missing files, whether it searches the entire repository, or if any filtering is applied beyond the optional constraint_types parameter. The description adds some clarity by defining constraints, but does not reveal side effects or edge cases.

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 a single, front-loaded sentence that efficiently communicates the tool's purpose without extraneous words. It earns a high score for being concise and structured.

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?

Given the tool's simplicity (read operation, 2 parameters, no output schema), the description is mostly complete. It states what the tool does and the schema covers parameter details. However, it does not specify the return format or behavior when no constraints are found, which could leave some ambiguity for the agent. Still, for a straightforward getter, it is adequate.

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 description coverage is 0%, so the description must compensate. It does so by explaining that constraints include 'linting rules, patterns, conventions', which helps interpret the constraint_types enum. However, it does not explicitly map parameters or explain the file_path semantics beyond the name. The schema itself provides the enum values, offering adequate baseline coverage.

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 clearly states the tool retrieves constraints for a file, using the verb 'Get' and specifying the resource and scope. It also clarifies what constraints are (linting rules, patterns, conventions). However, it does not explicitly distinguish from the sibling tool 'get_agents_md_constraints', which may overlap in purpose for specific files.

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 usage when constraints for a file are needed, but provides no explicit guidance on when to use this tool versus alternatives like 'get_agents_md_constraints' or when not to use it. It lacks exclusions and alternative recommendations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.