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mockzilla_docs_topics

List available Mockzilla docs topics with summaries, covering product and engine guides. Use it to locate relevant documentation before answering questions.

Instructions

List the Mockzilla docs that ship with this bridge: the product docs from mockzilla.org (what a simulation is, deploying, resilient backends, billing, settings, the CLI and this MCP server) and the open-source engine docs under engine/ (configuration, contexts, middleware, replay). Returns each category with its topics' id, title and one-line summary. The docs are files inside the bridge, so this needs no network and no login. Call it before answering a question about Mockzilla, then read the topics that fit.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

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 full behavioral disclosure. It states that the docs are files inside the bridge, requiring no network or login, and describes the output format. This covers the key behavioral traits—read-only, offline, and deterministic. Some minor aspects like potential size limits or pagination are not mentioned, but for a simple listing tool this is adequate.

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 three sentences, front-loaded with the core purpose, followed by output details and a usage tip. Every sentence earns its place: purpose, content breakdown, key behaviors, and when to call it. No redundancy or fluff.

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-parameter, no-output-schema tool, the description is fully complete. It specifies what the tool returns (categories with id, title, summary), the content scope, the operational context (no network/login), and even gives usage guidance. An agent has everything needed to invoke and interpret the result correctly.

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 has zero parameters, and the schema coverage is 100%, so the description adds no parameter-specific meaning. According to the rubric, a 0-parameter tool gets a baseline of 4. The description's mention of output categories doesn't compensate for missing params (none exist), so it remains at baseline.

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 clearly states the specific verb 'List' and resource 'Mockzilla docs', and distinguishes itself from siblings like mockzilla_docs_read and mockzilla_docs_search by describing its unique output (categories with topics' id, title, summary). It also specifies the scope (product docs and engine docs), making its purpose unmistakable.

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?

The description explicitly instructs 'Call it before answering a question about Mockzilla, then read the topics that fit,' which provides a clear when-to-use directive. It implies a follow-up step (reading topics) without explicitly naming the read tool, but the context is unambiguous. It doesn't state exclusions (when not to use), but the positive guidance is strong.

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