Pet Data Station

get_topic_context

Fetch one topic's RAG context (~200-500 tokens): source-verified claims (verbatim for Open-Access / public-domain sources, paraphrased derived summaries for copyrighted veterinary references) plus structured source citations (authority/title/url) and a trust block (raw trust axes + computed display_grade for this topic). Discover topic_ids with search_pet_topics first.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`topic_id`	Yes

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

TDQS

A4.6/5.0

Behavior4/5

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

With no annotations present, the description carries the full burden. It discloses key behavioral traits: token range (~200-500), source-verified claim types (verbatim vs paraphrased), citation structure, and the trust block. It does not mention error cases or explicit read-only status, but the fetch nature and detailed output coverage provide substantial transparency.

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 a single dense paragraph but every phrase adds value: token budget, claim handling, citation components, trust block, and sequencing. It is not wasteful, though slightly longer than strictly necessary due to parenthetical details.

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 moderate complexity, the description covers the input, the output structure (including trust axes and display_grade), and the required preceding step. An output schema exists, so return values are further documented, making the description complete for agent invocation.

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 0%, so the description must compensate for the sole parameter (topic_id). It does so by explaining that the tool fetches 'one topic' and directing the agent to search_pet_topics to obtain valid topic_ids. This adds meaningful context beyond the bare schema, though it stops short of specifying format or constraints.

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 uses a specific verb ('Fetch') and resource ('one topic's RAG context'), and clearly distinguishes from siblings by naming the discovery tool ('Discover topic_ids with search_pet_topics first'). It also outlines the return contents, making the tool's scope unambiguous.

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 states to use search_pet_topics first to discover topic_ids, providing clear sequencing guidance and implicitly excluding direct use without a known topic_id. This directly addresses when to use this tool versus alternatives.

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 targets a distinct resource or action: breed bans, nutrient values, nutrient comparisons, ADE stats, recalls, topic search, topic context, and feedback. Even the two nutrient tools (get_nutrient_value vs. compare_nutrient_standards) are clearly separated by single-value vs. multi-standard comparison, and search_pet_topics vs. get_topic_context are search-vs-retrieve.

Naming Consistency4/5

All tool names use snake_case and a verb_noun structure (check_, compare_, get_, search_, submit_). However, the verbs vary (check, compare, get, search, submit) rather than following a single verb family, and three tools start with 'get' while two start with 'search', which is slightly less uniform than a fully consistent pattern but still predictable.

Tool Count5/5

With 8 tools, the server is well-scoped. The set covers core retrieval operations (search, get context), domain-specific queries (breeds, nutrients, ADE, recalls), and a feedback mechanism. Each tool earns its place without redundancy or bloat.

Completeness4/5

The surface covers the apparent domain: searchable topics, detailed context retrieval, and specialized lookups for common pet regulatory questions. A minor gap is that there is no explicit tool to list all available jurisdictions, standards, or categories, but search_pet_topics with category filters and the feedback tool mitigate this. No critical dead ends.

Resources

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