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SqueezeOS — Institutional AI Market Intelligence

Inspect Capability

inspect_capability
Read-onlyIdempotent

Inspect one live capability by sml_id. Returns its real endpoint/payment metadata and, when safe, a real liveness probe rather than an invented reliability score.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
probeNo
sml_idYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed6 schema fields changed
    • addedInput schema / additionalProperties
      Added value: +false
    • addedInput schema / properties / probe / default
      Added value: +true
    • removedInput schema / properties / probe / description
      Removed value: -"Attempt a real liveness probe when safe to do so (default true)"
    • removedInput schema / properties / sml_id / description
      Removed value: -"The sml_id from a mesh_discover result"
    • addedInput schema / properties / sml_id / maxLength
      Added value: +500
    • addedInput schema / properties / sml_id / minLength
      Added value: +1
  2. Added

TDQS

A4.2/5.0
Behavior4/5

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

The annotations already establish read-only, idempotent, non-destructive behavior. The description adds meaningful behavioral context beyond that: it performs a real liveness probe only when safe, and it explicitly avoids returning an invented reliability score, which is valuable honesty about its execution behavior.

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?

A single sentence, front-loaded with the core action and identifier, then the key outputs and a meaningful disclaimer. Every clause earns its place; there is no redundant wording or repetition of schema fields.

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 read-only inspection tool, the description explains the key input, output, and situational caveat. The only minor gap is the vagueness of 'when safe,' but the rich annotations and simple signature keep this from being a significant omission.

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?

With 0% schema description coverage, the description carries the burden of explaining parameters. It clarifies that sml_id selects the capability and that a liveness probe is performed when it is safe, which maps to the probe boolean. It does not explicitly name the probe parameter, but the semantics are sufficiently conveyed.

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 the tool inspects one specific live capability identified by sml_id, and names the concrete outputs: endpoint/payment metadata and a real liveness probe. This distinguishes it from broader discovery or comparison tools without requiring schema inspection.

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 intended use is implied: use this when needing details about one specific capability rather than discovering or calling capabilities. However, it does not explicitly say when to prefer this over sibling tools like capability_manifest or discover_capabilities, nor does it state exclusions.

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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TDQS

A4.1/5.0
Disambiguation4/5

Most tools have clear boundaries: discover searches, inspect examines one, compare contrasts, recommend interprets natural language, and call executes. Some ambiguity exists between capability_manifest and discover_capabilities for inventory listing, and recommend_capability could be confused with discover_capabilities, but descriptions generally prevent misselection.

Naming Consistency4/5

All names are lowercase snake_case, and the core capability operations follow a verb_noun pattern. The noun-led capability_manifest, system_status, and x402_* resources deviate from that pattern, and capability names mix singular and plural, but the naming remains readable and internally consistent per subdomain.

Tool Count5/5

Ten tools is well within the ideal range and each tool maps to a distinct part of the capability discovery, comparison, payment, and execution workflow. There are no obviously redundant or throwaway tools, so the count feels appropriately scoped.

Completeness5/5

The set covers the full read-only market-intelligence lifecycle: inventory, search, inspect, compare, recommend, call, payment readiness, contract lookup, and settlement evidence. Operator CRUD is explicitly outside scope, so there are no meaningful dead ends for an agent using this surface.

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