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mayeu20

nerdychefs-mcp

search_prompts

Search the prompt library to find prompts for a task, filtering by category, persona, or tag. Get relevant results and include full prompt text when needed.

Instructions

Find prompts for a task, with optional category, persona, and tag filters.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagNo
limitNo
queryYes
personaNo
categoryNo
include_prompt_textNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure, but it only says 'find prompts.' It does not mention what include_prompt_text does, how results are ordered or limited, or what happens when no prompts match. The description reveals little beyond the basic search action.

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 description is a single sentence with no filler, and the core action plus the main optional filters are front-loaded. It is concise, though slightly under-specified for the number of parameters the tool accepts.

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

Completeness2/5

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

For a tool with six parameters, no annotations, and no output schema, this one-sentence description is not enough. It omits key usage details such as query requirements, limit behavior, include_prompt_text semantics, and relationship to sibling tools. An agent would need to inspect schemas or guess.

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. It clarifies that category, persona, and tag are filters, but it says nothing about the required query parameter, the limit default/maximum, or the meaning of include_prompt_text. It adds partial value but leaves several parameters unexplained.

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 uses the specific verb 'Find' with the resource 'prompts' and names the optional filters (category, persona, tag), which clearly indicates a search/listing operation. It does not explicitly distinguish from siblings like get_prompt or random_prompt, but the name and filter list make the purpose reasonably clear.

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 phrase 'for a task, with optional filters' implies this is the right tool for searching with criteria, but the description does not state when to prefer it over get_prompt, random_prompt, or the list_* tools. Usage context is implied rather than explicit.

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