Skip to main content
Glama

sumo_qa_deciding_approach

Selects the canonical QA approach for a user's intent by loading classifications and approaches, then routes to the matching sub-skill for further catalogues.

Instructions

Use first after using-sumo-qa on any QA intent. Loads classifications + approaches (the two needed to route), then reasons over the user's intent to pick the canonical approach and routes to the matching sub-skill (which loads any further catalogues on demand).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.42.0

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description carries the full disclosure burden, and it does well: it reveals the two catalogues loaded, that a reasoning step happens, that control is handed to a sub-skill, and that further catalogues are loaded on demand. It does not say what is returned to the agent or how the routing decision is surfaced, which is the remaining gap.

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?

A single sentence, front-loaded with the usage directive before the mechanics, and no sentence is filler. The parenthetical asides ('the two needed to route', 'which loads any further catalogues on demand') add density that makes the sentence slightly hard to parse on first read.

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 zero-parameter router with no annotations and no output schema, the description covers the essential contract: when to call it, what it loads, what it decides, and where it delegates. What the call yields to the agent is left implicit, which keeps it just under fully complete.

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?

The tool takes zero parameters, so there is nothing for the description to disambiguate and the baseline of 4 applies. It implicitly tells the agent that the input is the conversational/intent context rather than arguments.

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 names a concrete action chain: load classifications + approaches, reason over intent, pick the canonical approach, and route to the matching sub-skill. This distinguishes it from the plain loaders (sumo_qa_load_classifications / sumo_qa_load_approaches) and from the individual QA sub-skills. It falls short of 5 only because terms like 'canonical approach' and 'sub-skill' are internal jargon not defined here.

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?

'Use first after using-sumo-qa on any QA intent' gives an explicit sequencing rule relative to a named sibling, which is exactly the routing guidance an agent needs. It stops short of 5 because it offers no when-not-to-use condition and never states whether it should be re-invoked if intent changes mid-session.

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