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Glama

Get questions to ask the user

clarifying_questions
Read-onlyIdempotent

Use this when you want to know what user-facing questions would most tighten an existing quote. Returns structured questions ranked by price_impact (high / medium / low) so the calling agent can decide whether asking is worth a turn. The agent should render these as user-choices, not as covert data collection.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
quote_idYes
max_questionsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusYes
messageNo
questionsNo

TDQS

A4.4/5.0
Behavior5/5

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

Annotations already indicate safe, read-only, idempotent behavior. Description adds important behavioral details: questions are ranked by price_impact, and the agent should present them as user-choices rather than covert data collection. No contradiction with 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?

Three sentences, each serving a distinct purpose: usage, return format, and rendering guidance. No redundancy, well front-loaded. Every sentence earns its place.

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 simplicity (2 params, no enums, no nested objects) and existence of an output schema, the description covers purpose, usage guidelines, behavioral transparency, and ethical use. No gaps identified.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so description must add meaning. It implies 'quote_id' via 'existing quote' but does not explicitly describe either parameter. 'max_questions' is not mentioned at all. The schema's limited meaning (quote_id as string) is not enriched.

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?

Clearly states verb 'get' and resource 'questions to tighten an existing quote'. Distinguishes from sibling tools that create proposals or refine quotes. The description is specific about the task and outcome.

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?

Explicitly says when to use ('when you want to know what user-facing questions would most tighten an existing quote') and provides advice on rendering questions as user-choices. It does not explicitly exclude alternative scenarios but gives clear usage context.

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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TDQS

A4.3/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose, with descriptions that prevent confusion. Tools like scan_site and run_site_audit are differentiated by their focus on AI-readiness vs. site quality.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in snake_case, with clear action words like 'scan', 'create', 'get', 'verify'. Even longer names like 'summarize_scan_for_humans' maintain consistency.

Tool Count4/5

22 tools is slightly above the ideal range but justified by the comprehensive scope of the server, covering scanning, analysis, quoting, file delivery, and verification. Some tools like generate_files and get_customer_files could overlap but serve different contexts.

Completeness5/5

The tool surface covers the entire workflow from site scanning to deployment verification, with no obvious dead ends. All necessary operations for making a site agent-ready are present, including edge cases like x402 validation and credential verification.