list_cost_decodersList the 'real cost' decoders — topics where the advertised sticker price hides the true bill (e.g. AI customer support billed per resolution, where a $29/mo seat price becomes hundreds/mo at volume). Each entry carries the question it answers, the scenarios it computes, the vendor count and the data's as-of date. Pass a topic slug to get_cost_decoder.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the tool as read-only and idempotent, so the description adds context by explaining the content of each entry (question, scenarios, vendor count, as-of date). 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single coherent paragraph that front-loads the concept and includes an illustrative example. It could be slightly shorter but is well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema, the description covers what each entry contains (question, scenarios, vendor count, as-of date). It also hints at the data's real-world context (sticker price vs true bill). Adequate for a listing tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters; the input schema is empty. Per guidelines, baseline is 4. The description correctly indicates no input is needed beyond the implicit listing.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists 'real cost' decoders, providing a concrete example of AI customer support pricing. It distinguishes from the sibling get_cost_decoder by mentioning passing a topic slug to that tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for browsing available decoders, and directs users to get_cost_decoder for a specific slug. However, it does not explicitly state when to avoid using this tool or compare with other list 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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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.
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.
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.
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.