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Glama

triage_issue

Read-onlyIdempotent

Retrieve possible checks for blank Offerwall or reward callbacks from customer issue text. Returns candidate categories, questions, and sources, not a confirmed root cause.

Instructions

Retrieve possible checks for blank Offerwall or reward callbacks.

issue_text must contain customer prose, not an issue ID. For a recorded issue, retrieve its message with get_account_context or use draft_ticket(issue_id). Lexical baseline, not semantic diagnosis; negation/paraphrases can fail. Returns candidate categories, questions and sources, never a confirmed root cause.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
issue_textYes
integration_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.30.1

TDQS

A4.4/5.0
Behavior5/5

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

Annotations already declare readOnly, idempotent, closed-world and non-destructive, and the description adds substantive behavioural context beyond them: it is a lexical (not semantic) baseline, negation and paraphrases can cause failures, and it returns candidates rather than a confirmed root cause. That sets accurate expectations about reliability and output nature.

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?

Four short sentences, each earning its place: scope, input requirement, alternative routes, and known limitations. The most decision-critical content (what it returns and what it does not) is front-loaded and there is no filler.

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?

An output schema exists, so return values need not be spelled out, and the description still usefully summarises the candidate-level output. Input semantics, limitations and alternative tools are covered; the only gap is the undocumented optional integration_id parameter.

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 0%, so the description carries the burden. It does explain issue_text richly (customer prose vs issue ID), but integration_id is never mentioned, leaving half the parameters undocumented anywhere. Partial compensation for the coverage gap.

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 with narrow scope: retrieve candidate checks for blank Offerwall or reward callbacks. It also distinguishes itself from neighbours by describing what it returns (candidate categories, questions, sources) versus a confirmed diagnosis. The term "checks" is slightly abstract, so it falls just short of a fully self-explanatory purpose.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

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

Explicitly states the input precondition (issue_text must be customer prose, not an issue ID) and names the alternative routes for a recorded issue: get_account_context or draft_ticket(issue_id). This is precisely the when-to-use / when-not-to-use routing an agent needs to avoid calling it with a wrong identifier.

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