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Own Your AI

list_tools

Every Own Your AI tool: what it does, which platform it runs on, and whether it is free, members-only, or still coming. These run on the user's own machine.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusNoOptional filter: featured, free, paid, coming-soon

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.2/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that tools run on the user's own machine, which is a useful behavioral note, but it does not disclose whether the tool returns cached data, if it requires network access, or if it lists only currently available tools versus those in development. For a read-only list tool, this is a moderate gap given no annotations.

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 one sentence that packs in the core information (scope, content, platform, pricing availability) and a second sentence adding the local-machine context. It is front-loaded with the essential purpose. No redundancy, and it earns its length.

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

Completeness3/5

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

The tool is simple (one optional parameter, no output schema, no nested objects), and the description covers the purpose and the key contextual note about local execution. However, it does not specify whether the list is sorted, if it includes deprecated tools, or how the 'status' filter interacts with the listing (e.g., does it filter by all listed attributes or just pricing?). For a simple tool, this is borderline adequate but leaves minor gaps.

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?

The schema already describes the 'status' parameter with an enumerated list of possible values (featured, free, paid, coming-soon), so schema coverage is 100%. The description does not add any additional semantics beyond what the schema provides, so a baseline of 3 is appropriate.

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 clearly states the resource ('Every Own Your AI tool') and the information provided (what it does, platform, pricing availability). It distinguishes from siblings by focusing on listing all tools, whereas get_tool likely focuses on a single tool. A slight deduction for not explicitly contrasting with siblings, but the purpose is evident.

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 description implies the tool is for browsing all tools, and the optional 'status' filter suggests when it might be used to filter by status. No explicit exclusions or alternatives are given, but the context of siblings like get_access_and_pricing and get_tool suggests this is the list-all entry point. Usage guidance is implicit rather than explicit.

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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