Skip to main content
Glama

GAIP — evidence on AI agents before and after you call them

by io.github.tjcgraham-rgb
OverviewDiscussionsAdmin

Watch an agent or MCP server for changes

gaip_watch

Use this when asked to keep an eye on an agent or MCP server, or to be alerted when it changes. Pass its url: returns feed links and its latest dated changes; add webhook_url for a free watch (checked every 24 h, signed webhook on change). Free, no account; with a webhook it records a watch. Inputs must be public and non-personal.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesPublic https URL of the MCP server endpoint or agent (card) to follow. No query string.
verboseNoOptional: true returns the full result with every underlying field. Default: a short answer.
webhook_urlNoOptional: your own public https endpoint. GAIP then registers a watch and POSTs a signed event when the result changes.
continuity_handleNoOptional: the continuity_handle from an earlier GAIP result; links this call to your earlier ones (needed to see or remove your watches later).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / verbose
      Added value: +{
+  "default": false,
+  "description": "Optional: true returns the full result with every underlying field. Default: a short answer.",
+  "type": "boolean"
+}
  2. Added

TDQS

A4.4/5.0
Behavior5/5

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

The description adds substantial context beyond annotations: it states the tool is free with no account, that adding a webhook records a watch (consistent with readOnlyHint=false), the 24-hour check frequency, signed webhook behavior, and the public/non-personal input constraint. This goes well beyond the safety profile already provided by annotations.

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, dense paragraph that front-loads the usage scenario and then efficiently covers mechanics, cost, and constraints. Every sentence earns its place with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (creating watches, optional webhooks, continuity handles) and the absence of an output schema, the description adequately explains return values ('returns feed links and its latest dated changes'), side effects, and input constraints. The remaining parameter details are fully covered by the schema.

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%, so the baseline is 3. The description adds meaningful semantics for url ('Pass its url') and webhook_url ('add webhook_url for a free watch, checked every 24 h, signed webhook on change'), but does not elaborate on verbose or continuity_handle beyond what the schema provides.

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 (watch) and resource (agent or MCP server), and clarifies the outcome: feed links and latest dated changes. It does not explicitly differentiate itself from siblings like gaip_check or gaip_verify, 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 Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives a clear trigger: 'Use this when asked to keep an eye on an agent or MCP server, or to be alerted when it changes.' No when-not conditions or named alternatives are provided, so it is not a 5.

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

All GAIP — evidence on AI agents before and after you call them toolsInspect
Try in Browser
Shareable, User-Owned Context BackendPeople, applications, and agents read, write, and coordinate together in one context lake. Reach it over MCP, a CLI, a Python SDK, or REST.fulcradynamics.comAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources