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Recommend tools

recommend_tools
Read-onlyIdempotent

Ranked best-fit tools for a goal, with why + caveat. Follows this ask only — saved tags do not change the ranking. On a new user's first call, also returns short onboarding questions (project types, platforms, budget, preferences, tools in use) for you to ask, then call set_preferences with tags only.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "goal": "<goal>"
    },
    "name": "recommend_tools"
  }
}

Input Schema

NameRequiredDescriptionDefault
goalYes
limitNo
budgetNo'free' or max USD/mo
offsetNo
verboseNo
can_codeNo
platformNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior4/5

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

The annotations already establish read-only, idempotent, and closed-world behavior. The description adds meaningful context beyond that: results include why and caveat, saved tags do not affect ranking, and a new user's first call returns onboarding questions that should be followed by set_preferences.

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?

It is two compact sentences with the ranking behavior front-loaded and the first-call flow clearly appended. The phrasing is dense but each sentence carries useful information; minor ambiguity comes from 'Follows this ask only.'

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?

For a read-only recommendation tool with no output schema, the description explains the returned content and the onboarding return path, which is helpful. It is still incomplete because most of the seven parameters are left unexplained despite very low schema description coverage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 14%, with 7 parameters and only budget documented in the schema. The description mentions the goal implicitly but adds no meaning for limit, offset, verbose, can_code, platform, or how budget should be supplied, so it does not compensate for the coverage gap.

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 states a specific action and output: 'Ranked best-fit tools for a goal, with why + caveat.' This distinguishes it from a raw search, but it does not explicitly contrast it with siblings such as compare_tools or list_alternatives.

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?

It gives useful scoping guidance: 'Follows this ask only — saved tags do not change the ranking,' and explains the first-call onboarding flow plus the follow-up call to set_preferences. However, it never states when to use this tool instead of search, compare_tools, or list_alternatives.

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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