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Kiln

Kiln

by codeofaxel
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

match_design_requirements

Read-only

Scans a natural-language description to identify applicable functional requirements and returns matched constraint sets with rules and guidance before drafting a design brief.

Instructions

Identify which functional requirements apply to a design task.

        Scans natural language for requirement triggers (load bearing,
        watertight, outdoor, food safe, heat resistant, flexible, impact
        resistant, precision, aesthetic) and returns matched constraint
        sets with rules and guidance.

        Use this to understand WHAT constraints apply before getting
        the full design brief.

        Args:
            description: What the object needs to do (e.g. "outdoor
                hook that holds a heavy hanging planter").

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": {
      "description": "<description>"
    },
    "name": "match_design_requirements"
  }
}

Input Schema

NameRequiredDescriptionDefault
descriptionYesWhat the object needs to do (e.g. "outdoor hook that holds a heavy hanging planter").

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.5.1
    • addedInput schema / properties / description / description
      Added value: +"What the object needs to do (e.g. \"outdoor hook that holds a heavy hanging planter\")."
  2. First observedv0.1.0

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds value beyond that by disclosing the mechanism (natural-language trigger scanning) and the return content (matched constraint sets with rules and guidance), which the annotations do not convey.

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 purpose and trigger list are front-loaded, and the usage hint follows logically. The Args block largely restates the schema's parameter description, which is mild redundancy but not enough to hurt readability.

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?

With no output schema, the description carries the burden of explaining returns, and it does so ('returns matched constraint sets with rules and guidance'). For a single-parameter read-only tool this is nearly complete; only the no-match behavior and sibling differentiation are missing.

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?

Schema description coverage is 100% and the single parameter is fully documented in the schema, so the baseline is 3. The description's example phrasing and trigger keyword list add modest guidance on how to phrase the input, but nothing beyond what the schema already states about the parameter itself.

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?

States a specific verb and resource ('Identify which functional requirements apply to a design task') and enumerates the trigger categories it scans for, so the agent knows exactly what the tool does. It does not, however, distinguish itself from close siblings like analyze_design_requirements or validate_design_for_requirements, which an agent could easily confuse it with.

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?

'Use this to understand WHAT constraints apply before getting the full design brief' gives a sequencing hint (call this early), which is useful context. But there is no explicit when-not guidance and no mention of the near-identical sibling tools, leaving the agent to infer which of the requirements tools to pick.

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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