Skip to main content
Glama

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

by io.github.tjcgraham-rgb
OverviewDiscussionsAdmin

Why did my agent or API call fail?

gaip_diagnose
Read-onlyIdempotent

Use this when an agent, MCP or API call failed. Paste the error text and/or http_status; add the service url if known. Returns the cause, the exact fix (e.g. the missing argument) and retry_after_seconds; keep_receipt: true adds a dated receipt. Free, read-only, no account; inputs must be public and non-personal.

Input Schema

NameRequiredDescriptionDefault
urlNoOptional: public https URL of the agent, MCP server or API that failed.
errorNoThe error you got, as text: HTTP status line, JSON-RPC/A2A/MCP error or message. Give this and/or http_status.
verboseNoOptional: true returns the full result with every underlying field. Default: a short answer.
http_statusNoOptional: the HTTP status code you got, e.g. 429.
keep_receiptNoOptional: true keeps a dated GAIP receipt of this answer and returns a continuity handle. Default: GAIP keeps no record of the task (usage is counted without its content).
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 / keep_receipt
      Added value: +{
+  "default": false,
+  "description": "Optional: true keeps a dated GAIP receipt of this answer and returns a continuity handle. Default: GAIP keeps no record of the task (usage is counted without its content).",
+  "type": "boolean"
+}
  2. 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"
+}
  3. Added

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already cover readOnly/idempotent/non-destructive, and the description adds substantive context on top: the return payload (cause, exact fix, retry_after_seconds), the receipt behavior, and hard input constraints ('must be public and non-personal', 'no account'). Minor gaps remain on failure modes and whether any input combination is invalid.

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?

Front-loaded with the usage trigger, then inputs, then outputs, then constraints — a logical order with no filler sentences. The semicolon-chained clauses are dense but every clause carries information.

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?

With no output schema, the description usefully summarizes the return values and the verbose toggle, and it discloses privacy/account constraints. Slightly incomplete: continuity_handle's purpose (linking to earlier/watches) is only implied, not explained in the description.

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?

Schema description coverage is 100%, so the baseline is 3. The description mostly mirrors the schema ('paste the error text and/or http_status', 'add the url if known') and only marginally extends it via the keep_receipt receipt effect and privacy constraint; the nested continuity_handle is left entirely to the schema.

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 up front: diagnose a failed agent, MCP or API call. The trigger ('when an agent, MCP or API call failed') makes the scope unambiguous. It does not, however, distinguish itself from siblings like gaip_check or second_look_check.

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?

Gives a clear triggering condition ('Use this when an agent, MCP or API call failed') and tells the agent what to supply (error text and/or http_status, url if known). No when-not guidance or explicit routing away from the sibling check/verify tools.

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