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agents-docs

agents-docs

by Lolaplex
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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list_docs

List indexed technical documents, fact sheets, API specs, and playbooks by category and size for AI coding agents. Filter by stacks, models, APIs, platforms, custom, or all.

Instructions

List all indexed technical documents, fact sheets, API specs, and playbooks with category and size.

Args: category: Filter by category ('stacks', 'models', 'apis', 'platforms', 'custom', or 'all')

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": "list_docs"
  }
}

Input Schema

NameRequiredDescriptionDefault
categoryNoall

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.44.1

TDQS

B3.4/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. Beyond the implied read-only nature of 'List', it says nothing about pagination, result limits, ordering, or auth requirements, which matters for a catalog-listing tool. 'with category and size' is the only return-behavior hint.

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?

One summary sentence plus a compact argument block; nothing is wasted. The front-loaded sentence carries the purpose, though the 'Args:' formatting adds minor structural noise.

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?

An output schema exists, so return values need not be explained, and the single optional parameter is documented. Only pagination/scope limits are unaddressed; otherwise complete for a simple listing tool.

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?

Schema description coverage is 0% – the schema only declares a string with default 'all' and no enum. The description compensates by enumerating the valid values ('stacks', 'models', 'apis', 'platforms', 'custom', 'all'), adding meaning the schema lacks.

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 ('indexed technical documents, fact sheets, API specs, and playbooks'), so the agent knows exactly what it returns. It does not, however, distinguish itself from the sibling search_docs or list_catalog, leaving the enumeration-vs-search boundary to inference.

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?

'List all indexed...' implies enumerating the full catalog, which hints at when to prefer it over search_docs. There is no explicit when-to-use/when-not statement or named alternative, so the routing guidance is only implied.

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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