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Lufi AI trust scores

search_tools

Read-only

Find AI tools on Lufi with their independent trust scores. Filter by free text (name or task), intent (productivity, creative, analytical, agentic), compliance label (e.g. SOC 2, HIPAA, GDPR), the AI company a tool runs on (e.g. Anthropic), official MCP server, or free plan.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "search_tools"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNo
queryNoTool name or task, e.g. 'image generation'
intentNo
has_mcpNoOnly tools with an official MCP server
runs_onNoAI company the tool is confirmed to run on, e.g. 'OpenAI' or 'Anthropic'
free_planNoOnly tools with a free plan
complianceNoCompliance label, e.g. 'HIPAA'

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds that results carry trust scores, which is genuine context, but says nothing about ordering, how multiple filters combine (AND vs OR), or what happens when limit is hit — behavior an agent needs for a multi-filter search.

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?

Two sentences, front-loaded with what the tool returns before the filter list. The filter enumeration is somewhat redundant with the schema and could have been trimmed, but it aids fast scanning of the query's capabilities.

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?

No output schema exists, so the description is the only source for return-value expectations; it names 'trust scores' but not the rest of the result shape or result-set size behavior. For a 7-parameter search tool, the absence of filter-combination and pagination details leaves a real gap.

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?

With 71% schema description coverage, the baseline is 3. The description restates the same filter meanings already present in the schema (has_mcp 'official MCP server', runs_on examples, compliance examples) rather than adding new semantics, and it omits the 'limit' parameter entirely, including its max of 25.

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?

States a specific verb and resource ('Find AI tools on Lufi') plus a distinctive output attribute ('independent trust scores'), which is more informative than the name alone. It never contrasts itself with the siblings 'get_tool' or 'compare_tools', so an agent must infer that this is the discovery/browse entry point rather than the detail or comparison one.

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?

Usage is only implied through the enumerated filter axes ('Filter by free text..., intent..., compliance label...'), which sketch when each narrowing applies but never state when to prefer this over get_tool. There are no exclusions, prerequisites, or explicit 'use X instead when...' routing.

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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