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Glama
woodydaniel

whodoicallfor-mcp

by woodydaniel

get_scenario

Read-onlyIdempotent

Retrieve a complete home emergency scenario using its category and slug. Returns who to call, estimated costs, FAQ, sources, and a full step-by-step markdown guide.

Instructions

Fetch one situation in full: structured answer (who to call, costs, FAQ, sources) plus the complete step-by-step guide as markdown. Use category and slug values from route_emergency or list_scenarios.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesScenario slug, e.g. "ceiling-leaking"
categoryYesCategory slug, e.g. "water"

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
faqNo
urlYes
tldrYes
costsNo
titleYes
sourcesNo
updatedNo
categoryYes
json_urlNo
verticalNo
descriptionNo
who_to_callNo
body_markdownNoThe full step-by-step guide as markdown
recommended_callNo

Schema Changelog

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

  1. First observedv1.0.0

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already indicate readOnlyHint=true, idempotentHint=true, destructiveHint=false. Description adds useful behavioral context by specifying the return format (structured answer + markdown guide). However, it doesn't mention performance characteristics or any dependencies on other tool calls if inputs are not from siblings.

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?

Description is concise (two sentences) and front-loaded with the primary purpose. Every word adds value - the first sentence explains what is returned, the second tells where inputs come from. No redundant language.

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 low complexity (2 required string params, no enums, no nested objects), the presence of both input and output schemas, and comprehensive annotations, the description is complete. It clearly explains what the tool returns and how to properly call it, leaving no ambiguity for an AI agent.

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 already covers both parameters with 100% coverage (category and slug). Description adds value by stating they are 'category slug' and 'scenario slug' with examples like 'water' and 'ceiling-leaking', which clarifies the role of each field beyond their type definitions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states it fetches one scenario with full details including structured answer, costs, FAQ, sources, and step-by-step guide as markdown. It distinguishes itself from siblings by specifying it retrieves a single scenario in full versus list_scenarios that lists multiple scenarios, and route_emergency which handles routing.

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 instructs to use category and slug values from route_emergency or list_scenarios, providing clear context on when to invoke this tool and where to get the required input parameters. This avoids confusion with its sibling tools.

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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