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Report your real experience of a service (strengthens its measured verdict)

aicom_report_telemetry

FREE. After you actually call a service/API/agent, report what you observed — did it work, how slow, did the response still match its shape. Your report is folded into that subject's RELIABILITY axis as a real-caller signal (weighted by your verification tier, deduped per reporter, Sybil-defended), which is what makes a measured verdict trustworthy: a service can fool aicomglobal's prober but not the agents actually calling it. NEVER include secrets or real payload values — response_shape is hashed to keys+types only. You are never charged. Reports are self-attested (advisory, not proof).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
okYesDid the call succeed?
subjectNoA public https URL you called, if it isn't a listing
latency_msNoRound-trip latency in milliseconds, if you measured it
offering_idNoThe listed offering you called (or use `subject`)
response_shapeNoA SMALL sample of the response — hashed to its shape (keys+types), never stored raw. No secrets/payload values.

Schema Changelog

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

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

No annotations provided, so description carries full burden. It discloses important behaviors: reports are self-attested, advisory, not proof; data is hashed and deduped; Sybil-defense; weighted by verification tier. This gives agents clear understanding of tool's properties.

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?

Description is detailed but every sentence contributes. It front-loads 'FREE' and clearly explains process. Could be slightly trimmed but remains efficient.

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?

Given 5 parameters and no output schema, description covers tool's effect on system, data handling, and important constraints. It is sufficiently complete for agent to use correctly.

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?

Schema coverage is 100%, and description adds key contextual info: never include secrets, response_shape is hashed. It reinforces purpose of each parameter without repeating schema verbatim.

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 action: reporting real experience of a service call. It uses specific verb 'report' and identifies the resource (service reliability). It is distinct from siblings like aicom_report by focusing on telemetry, though not explicitly differentiating.

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 description provides usage context (after calling a service) and warns against including secrets. However, it does not explicitly contrast with alternative reporting tools or specify when not to use it.

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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