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handmade

handmade

by h-hiram
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

handmade_list_tells

Lists all AI-design tells that handmade evaluates, including each tell's category, weight, reason, and fix, so you can identify and correct UI design issues.

Instructions

List every AI-design tell handmade checks for, with category, weight, reason and fix.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "handmade_list_tells"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.1

TDQS

A3.5/5.0
Behavior2/5

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

No annotations are supplied, so the description carries the full burden. It never states that the tool is read-only, whether the tell list is static or version-dependent, how results are ordered, or how many entries to expect. For a simple zero-parameter listing the risk is low, but the disclosure is thin.

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?

A single front-loaded sentence with no filler; the verb, the scope and the returned fields all appear immediately.

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 does the job of describing what comes back — the four fields per tell. It omits volume (how many tells), ordering, and any guarantee of stability, which keeps it from a 5 given the missing structured fields.

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?

The tool takes no parameters, so the baseline is 4. The sentence does add useful meaning about the shape of each returned entry (category, weight, reason, fix), which goes beyond the empty schema.

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 ('List') and resource ('every AI-design tell handmade checks for'), and enumerates the payload fields (category, weight, reason, fix), which distinguishes it from action-oriented siblings like handmade_check and handmade_scan. It stops short of naming a sibling explicitly, so it lands at 4 rather than 5.

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?

Usage is only implied: an agent can infer this is the reference/catalog tool used to learn what the checks look for, as opposed to running a scan. There is no explicit statement of when to call it, when not to, or which sibling to use for actual checking.

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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