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aegis

by com.borisinc
OverviewDiscussionsAdmin

smart_discover

Describe what you need in plain language; Aegis maps it to the best verified services (LLM intent matching). Paid $0.01 via x402.

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": {
      "query": "<query>"
    },
    "name": "smart_discover"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden. It usefully discloses the cost ($0.01 via x402) and the LLM intent-matching mechanism, but it does not explain the return format, what 'verified services' means, or any side effects or security considerations.

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 a single, front-loaded sentence that immediately tells the user what to do, followed by the mapping mechanism and cost. Every word earns its place, with no redundancy.

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 parameter, no nested objects), and the description covers the basic input and pricing. However, there is no output schema and no description of what the tool returns, which is a notable gap for an agent selecting and invoking the tool.

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 has one query parameter with no description, and schema coverage is 0%. The description adds meaning by explaining that the user should 'describe what you need in plain language', which maps directly to the query parameter. However, it lacks examples, constraints, or details about accepted formats.

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 tool maps plain-language requests to verified services via LLM intent matching, giving a specific verb and resource. It does not explicitly distinguish from the sibling tool 'discover', 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 phrase 'Describe what you need in plain language' implies the primary use case, but there is no explicit guidance on when to use this tool versus siblings like discover, procure, or route. No exclusions or alternatives are mentioned.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All aegis toolsInspect
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