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Nerdit

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by nerdit-ai
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Python
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list_guides

Retrieve the daemon's static agent guides with topics, titles, and summaries to identify which guide matches a user request.

Instructions

List this daemon's agent guides: {daemon_version, guides: [{topic, title, summary}]}.

    Static text shipped with the daemon, the same for every caller. Read
    ``get_guide('index')`` first: it says which guide fits the request.

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_guides"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.9.3

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral burden and does so well: it declares the data is static text shipped with the daemon and identical for every caller, telling the agent the result is non-personalized and safely cacheable. It doesn't discuss caching or freshness beyond "static," which is a minor residual gap.

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?

Two short sentences with the return shape front-loaded and the recommended call sequence second. Every clause earns its place and nothing is redundant.

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

Completeness5/5

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

For a zero-argument listing tool with no output schema, the description supplies the return structure inline along with the key behavioral fact (static, caller-independent) and the follow-up action. Nothing an agent needs in order to call and use it correctly is missing.

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 zero parameters, so there is nothing to disambiguate; the baseline applies. The description spends its words on output shape and sequencing instead, which is the right allocation for a parameterless call.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb and resource ("List this daemon's agent guides") and immediately gives the return shape {daemon_version, guides: [{topic, title, summary}]}, so the agent knows exactly what it gets. It also draws a boundary against the sibling get_guide by pointing there for guide content.

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?

It gives explicit routing guidance: read get_guide('index') first to learn which guide fits the request, which effectively frames list_guides as the enumeration step rather than the content-fetch step. It stops short of stating when this tool should not be used, but the alternative for content is clearly named.

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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