caddence

Get catalogue stats and valid filter values

get_catalog_stats

Live catalogue totals plus the valid values for search filters (brands, product types, conditions, flexes, hands, price range). Call this before filtered searches if unsure which brand or product_type spellings the catalogue uses.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`context`	Yes	Explain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): "Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization."

TDQS

A4.4/5.0

Behavior4/5

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

With no annotations, the description carries the burden of behavioral context. It discloses that the data is 'live' and specifies the exact categories of valid filter values, giving a realistic sense of what the tool returns. It does not explicitly mention read-only behavior, but 'stats' implies it.

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?

The description is two sentences long, each serving a distinct purpose: the first states what the tool does, the second provides usage guidance. No wasted words.

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 simple one-parameter tool with no output schema, the description adequately covers the tool's function and usage. It lists the filter types included, but does not specify the format of the return value or the exact meaning of 'catalogue totals'.

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

Parameters3/5

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

The schema covers the only parameter ('context') with a full description, so the baseline is 3. The tool description does not add any additional semantic information about the parameter, making it sufficient but not enhanced.

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 specifies what the tool does: returns live catalogue totals and valid filter values for brands, product types, conditions, flexes, hands, and price range. This is specific and distinguishes it from sibling tools like get_market_deals or get_price_history.

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?

The description explicitly advises to call this tool before filtered searches when unsure about catalog-specific spellings, which provides a clear when-to-use directive and indirectly references alternatives like search_golf_products.

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

A4.2/5.0

Disambiguation5/5

Each tool has a clearly distinct purpose: catalog stats for validation, deal intelligence for price quality, market deals for best values, price history for trends, product offers for purchase links, and search for initial product discovery. No overlap or ambiguity.

Naming Consistency5/5

All tool names follow a consistent 'get_' prefix except 'search_golf_products', which uses 'search_'—this is appropriate as it's a broader discovery action while the rest retrieve specific data. The pattern is predictable and logically distinct.

Tool Count5/5

6 tools is perfectly scoped for a golf price comparison server: entry search, catalog metadata, deal finder, price quality, history, and offers. Each tool addresses a distinct task without redundancy.

Completeness5/5

The tool surface covers the full search-to-purchase workflow: product discovery (search_golf_products), catalog validation (get_catalog_stats), deal exploration (get_market_deals, get_deal_intelligence), historical context (get_price_history), and purchase links (get_product_offers). No obvious gaps.

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