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list_prompts

Lists saved AI prompts as metadata, filterable by category, tags, or keyword search for efficient context use.

Instructions

Lista prompts salvos (retorna apenas metadata para eficiência de contexto). Suporta filtros por categoria, tags ou busca. Use get_prompt para conteúdo completo.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNoFiltrar por tags específicas (opcional)
searchNoBuscar por palavra-chave no nome ou descrição (opcional)
compactNoSe true (padrão), retorna apenas metadata. Se false, inclui descrição completa.
categoryNoFiltrar por categoria específica (opcional)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.8/5.0
Behavior3/5

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

No annotations are provided, so the description must carry full behavioral burden. It mentions that by default it returns only metadata for context efficiency, and that the 'compact' parameter can change this, but it does not disclose side effects, rate limits, or authentication requirements. Since there are no annotations, a 3 reflects that it gives some behavioral context but is not comprehensive.

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 sentence that is front-loaded with the core action, followed by important caveats about metadata and an explicit pointer to get_prompt. No wasted words.

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 there is no output schema and the tool is a simple list operation with full schema coverage, the description provides enough context: it explains the default metadata-only return and points to get_prompt for full content. It could mention pagination or ordering, but those are not critical for correct invocation.

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 coverage is 100%, so the schema already documents all parameters thoroughly. The description does not add meaning beyond the schema, as it only repeats that filters are supported. Baseline 3 applies when the schema does the heavy lifting and the description does not compensate further.

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?

Clearly states what the tool does: lists saved prompts and supports filtering by category, tags, or search. Distinguishes itself from get_prompt by mentioning that get_prompt retrieves full content. However, it does not explicitly state that it returns only metadata as opposed to full content in the main clause, though it does say 'retorna apenas metadata'. It is mostly clear but lacks explicit differentiation from all siblings like get_categories.

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?

Provides a clear usage pointer: 'Use get_prompt para conteúdo completo', indicating when to use an alternative. However, it does not specify when to use this tool versus other list-like tools such as get_categories or get_tags, though those are for different resources.

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