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Launchpad HQ

Search AI tools

search_tools
Read-onlyIdempotent

Use this when the user wants to find AI tools for a task, optionally within a budget, skill level or platform. Returns Launchpad HQ catalog matches with dated, sourced free-tier facts where available.

Input Schema

NameRequiredDescriptionDefault
taskYesWhat the user wants to do, e.g. 'transcribe meetings' or 'make slides'.
limitNoMax results (1-10, default 5).
budgetNoBudget band. 'free' keeps only free or freemium tools.
skill_levelNoUser's skill level. Tools above it rank lower.
platform_typeNo

Output Schema

NameRequiredDescriptionDefault
noteYes
queryYes
resultsYes
data_as_ofYes
attributionYes
total_matchesYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already establish read-only, idempotent, closed-world behavior, so the safety profile is covered. The description adds genuine value by disclosing the result content ('Launchpad HQ catalog matches with dated, sourced free-tier facts where available'), telling the agent the data is curated and provenance-tagged rather than scraped live.

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 sentences, no waste, with the usage trigger front-loaded before the return-value note. Every clause carries information the agent can act on.

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?

With an output schema present, annotations covering safety, and 80% schema coverage, the description only needs to supply routing and return-shape context, which it does. Minor gaps remain: no guidance on what happens when nothing matches or on how 'free-tier facts where available' may be absent.

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?

Schema description coverage is 80%, so the schema already documents every parameter including enums and the limit range. The description only echoes the parameter names ('budget, skill level or platform') without adding filtering or ranking nuances, which is the baseline expectation.

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 verb+resource ('find AI tools for a task') plus the qualifying dimensions (budget, skill level, platform), so the agent knows exactly what the tool returns. It does not name or differentiate from siblings like find_free_alternatives, which overlaps on the 'free' axis, so it falls short of a 5.

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 trigger condition is stated ('use this when the user wants to find AI tools for a task'), which is clear enough for the primary case. However, no exclusions or alternatives are named — the agent is left to decide on its own between this, find_free_alternatives, and get_pricing_facts.

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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