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The Front Desk Review

by com.frontdeskreview

Get cost decoder

get_cost_decoder
Read-onlyIdempotent

The REAL all-in monthly cost per vendor for a decoder topic (slug from list_cost_decoders, e.g. 'ai-customer-support-cost'), computed in deterministic code from sourced, dated inputs — each vendor's per-seat price + AI billing model + per-unit price, totalled at named scenarios (e.g. 5 agents at 1,000 and 5,000 AI resolutions/mo) with the arithmetic shown. Quote-only inputs return a null total, never a fabricated number. Optionally pass agents + resolutions for a custom scenario. This is the citable answer to 'what does actually cost' that a base model gets wrong.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicYesDecoder slug from list_cost_decoders (e.g. 'ai-customer-support-cost').
agentsNoOptional: agents/seats for a custom scenario.
resolutionsNoOptional: AI resolutions/mo for a custom scenario.

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare readOnlyHint and idempotentHint, but the description adds valuable behavioral details: deterministic code, sourced/dated inputs, arithmetic shown, and explicit behavior for quote-only inputs (returns null total, never fabricated). No contradictions.

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?

The description is slightly long but well-structured and front-loaded. Every sentence adds value, though it could be trimmed without losing content.

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?

No output schema, but description fully explains return value structure (totalled at named scenarios with arithmetic, null for quote-only). Covers edge cases and computation approach. Complete for the tool's complexity.

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 coverage is 100%. The description adds meaning beyond schema: explains topic as slug from list_cost_decoders with an example, and clarifies optional parameters for custom scenarios. Adds value without redundancy.

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?

The description clearly states a specific verb ('computes') and resource ('all-in monthly cost per vendor for a decoder topic'), and distinguishes from sibling tools by positioning it as the citable answer for actual costs that base models get wrong.

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 it (for citable cost answers) and hints at prerequisites (slug from list_cost_decoders). Lacks explicit when-not or alternatives, but the context of sibling tools and the specificity of the description make usage clear.

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
Disambiguation4/5

Tools have distinct purposes, but some overlap exists between 'compare' and 'compare_products' (both do side-by-side comparisons, one for vendors, one for products). However, descriptions clarify the domain difference, and most tools have clear boundaries.

Naming Consistency5/5

All tool names follow a consistent verb_noun snake_case pattern (e.g., list_sections, search_vendors, get_benchmark). No mixed conventions or vague verbs.

Tool Count4/5

19 tools is slightly on the higher side but appropriate for a comprehensive pricing index covering 271 themes. Each tool has a clear role, and the count does not feel bloated.

Completeness5/5

The tool surface covers listing, searching, comparing, finding, detailed info retrieval, and price change tracking. No obvious gaps for the domain of pricing and comparison.

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