get_fertilizer_profileGet a structured public fertilizer product profile using the exact slug returned by search_fertilizers.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Exact safe slug path returned by the related Atlarium search tool. | |
| language | No | Optional preferred response language: it, en or es. |
| Name | Required | Description | Default |
|---|---|---|---|
| data | Yes | ||
| tool | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare the tool as read-only, idempotent, non-destructive, and not open-ended, so the behavioral baseline is well-covered. The description adds minimal behavioral context beyond this, merely stating it retrieves a 'public' profile. Since the annotations carry the burden, a score of 3 is appropriate as the description does not contradict and adds a bit of context (public nature) but no further details.
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 sentence that perfectly captures the essential purpose and key usage instruction (slug from search_fertilizers) without any wasted words. Every part of the sentence earns its place, making it highly concise and efficiently 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?
Given the low parameter count (2), high schema coverage (100%), comprehensive annotations (covers safety, idempotency, etc.), and the presence of an output schema, the description adequately covers the tool's role. It provides the critical context about slug origin, which compensates for what the schema doesn't capture. It could be more complete by noting any error handling or default behaviors for the language parameter, but it's sufficiently comprehensive for most use cases.
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?
Schema description coverage is 100%, meaning the schema already fully documents both parameters (slug and language) with their constraints, patterns, and descriptions. The description does not add new parameter meaning beyond referencing the slug's origin from 'search_fertilizers', which provides useful context for selecting the correct value but doesn't enhance semantic understanding of the parameters themselves. Thus, the baseline score of 3 is fitting.
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 retrieves a 'structured public fertilizer product profile' using a specific identifier ('slug'), which is a specific verb+resource combination. It also distinguishes this tool from the sibling 'search_fertilizers' by linking the slug input to that search tool, making its unique purpose and relationship clear.
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 explicitly specifies that the slug must be the exact one returned by 'search_fertilizers', which provides clear guidance on when and how to use this tool. However, it does not mention when not to use it or provide alternative tools for different scenarios (e.g., searching vs. retrieving a profile), leaving some implicit guidance.
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 has a unique name and clearly documented purpose. The 'get_' and 'search_' pairs are explicitly linked via slugs, and the 'calculate_', 'check_', 'convert_', 'generate_', 'list_', 'match_', and 'suggest_' tools all address distinct operations. There is no ambiguity or overlap.
All 39 tools follow a consistent verb_noun pattern in snake_case (e.g., calculate_tank_volume, search_plants, get_fish_profile). No mixing of conventions or non-standard naming is present.
With 39 tools, the set is far above the typical well-scoped range of 3-15. While the domain is broad, the sheer number makes the tool surface heavy and potentially overwhelming for an agent to navigate effectively.
The tool set covers the entire domain of an aquarium habitat database: calculations, unit conversion, species compatibility, profile retrieval for all entity types, diagnostic matching, and habitat suggestion. No obvious gaps exist for a read-only advisory API.