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gateway.request_capability

Describe a task in natural language to get ranked tool recommendations. Matches against installed CLIs and MCP servers, but does not start them.

Instructions

Recommend the right tool for a task — describe what you need in natural language. Examples: 'scrape a website', 'search Slack messages', 'query Postgres', 'browse the web'. Matches against installed CLIs and 90+ provisionable MCP servers and returns ranked candidates; it does NOT start anything — call gateway.provision to actually install/start the recommended server. Prefer this over gateway.provision when you don't already know the exact server name.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesNatural language description of the capability needed (e.g., 'I need to scrape a website', 'browser automation')
available_clisNoOptional: CLIs known to be available in the environment
Behavior4/5

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

With no annotations, the description fully explains that the tool returns ranked candidates by matching against CLIs and MCP servers. It explicitly states it does NOT start anything, making the non-destructive, advisory nature clear. Absent are details about return structure or limitations like rate limits, but these are minor for a recommendation tool.

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 extremely concise with three sentences: one explaining the tool's purpose with examples, one clarifying it doesn't execute, and one giving usage guidance. Every sentence adds value with no redundancy.

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?

For a simple recommendation tool with two parameters and no output schema, the description covers essential aspects: purpose, examples, non-execution behavior, and sibling differentiation. It mentions matching against 90+ provisional MCP servers, providing helpful context. Minor omissions like exact return format are acceptable given the tool's simplicity.

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 schema covers 100% of parameters, establishing a baseline of 3. The description adds value by providing contextual examples for the query parameter (e.g., 'scrape a website') and explaining the available_clis parameter's purpose. It also mentions that results are ranked candidates, going beyond schema.

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 this tool recommends the right tool for a task based on natural language description. It uses specific verbs ('Recommend', 'describe what you need') and distinguishes itself from sibling tool gateway.provision by clarifying it does not start anything.

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 advises preferring this tool over gateway.provision when the exact server name is unknown, providing clear when-to-use guidance. It also offers examples of queries, though it lacks explicit when-not-to-use scenarios beyond the contrast with provision.

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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