Compare one nutrient across 2-3 standards, e.g. standards='AAFCO_2024,FEDIAF_2025' (bare codes 'AAFCO,FEDIAF' = latest indexed edition). Other params as in get_nutrient_value.
| Name | Required | Description | Default |
|---|---|---|---|
| basis | Yes | ||
| species | Yes | ||
| nutrient | Yes | ||
| lifestage | Yes | ||
| standards | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry behavioral transparency. It only explains standards code syntax (bare codes = latest edition); it doesn't describe the output, constraints, or safe/read-only nature. This leaves significant behavioral ambiguity.
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?
Two concise sentences plus an example; front-loaded with the primary purpose. Every element adds value.
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 an output schema, the description leaves several invocation details to a sibling tool and doesn't cover parameter values. The bare-code shorthand is helpful, but the overall description is only minimally sufficient.
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?
Input schema has 5 string parameters with 0% description coverage. The description explains the format and alias behavior for 'standards' and directs to get_nutrient_value for the other parameters, but does not define acceptable values for species, lifestage, nutrient, or basis.
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?
States a clear action (compare) with object (one nutrient) and scope (across 2-3 standards). The example standards list and reference to get_nutrient_value disambiguate it from single-value sibling tools.
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?
Explicitly frames the task as comparison across standards and points to get_nutrient_value for shared parameters, establishing usage context. It does not explicitly state when not to use it or edge cases, but the compare-vs-single distinction is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.