fragrances

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

With no annotations provided, the description carries the burden of behavioral disclosure. It explains the matching logic (distinctive-note overlap) and the output behavior (returns matches with similarity ranking), which are useful behavioral traits. It does not cover edge cases like invalid slug or no matches, but for a read-only lookup tool this is acceptable.

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 highly concise, with two sentences that each add value: the first states the core functionality, the second specifies the ranking output. No redundant or extraneous words.

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?

For a simple one-parameter tool with no output schema or annotations, the description provides enough coverage: it explains the purpose, the underlying mechanism, and the return format. Minor gaps like error behavior or empty results are not mentioned, but these are not critical for a straightforward similarity search.

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 coverage is 100% as the single parameter 'slug' has a description with an example. The tool description does not add additional parameter-level context beyond repeating that it takes 'a given one'. Baseline for high schema coverage is 3.

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's function (find similar fragrances) with a specific mechanism (distinctive-note overlap) and output (similarity ranking). This distinguishes it from siblings like search_fragrance (likely name-based search) and fragrance_info (single-fragrance details).

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 usage: provide a fragrance slug to get similar fragrances. However, it does not explicitly discuss when to use this tool over siblings or include any when-not-to-use guidance. The intended scenario is evident but not explicitly contrasted with alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations provided, the description carries the burden of behavioral disclosure. It clearly implies a read-only lookup (returning a profile) and lists the response contents. It does not mention error handling or side effects, but none are expected for a simple get-by-slug operation. The description adds useful context about the source and scope, which is sufficient for this non-destructive tool.

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, front-loaded sentence with no wasted words. It efficiently packs all essential information: the action (full profile), the source (parfica.com), the key (slug), and the full list of returned fields. Every element earns its place.

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?

For a simple tool with one parameter and no output schema, the description is nearly complete. It enumerates all the data fields returned, which compensates for the missing output schema. It does not specify behavior for invalid slugs or edge cases, but given the low complexity, this is a minor gap.

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%: the input schema already documents the 'slug' parameter as 'Fragrance slug from search_fragrance, e.g. "creed-aventus"'. The description adds no extra parameter semantics beyond the schema, so the baseline score of 3 applies.

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 returns a 'Full profile of a fragrance on parfica.com by its slug' and enumerates the fields (brand, year, gender, concentration, family, note pyramid, accords, perfumers, community rating). This distinguishes it from sibling tools like search_fragrance (which finds fragrances) and find_dupes (which finds duplicates).

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 a prerequisite: the slug comes from search_fragrance, which guides the agent to use search_fragrance first. However, it does not explicitly state when not to use this tool or mention alternatives like find_dupes. The context is clear but lacks explicit exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations, the description carries the full burden. It discloses searchable fields (name in Latin/Cyrillic, brand, note, perfumer) and that results include links. However, it omits details like result ordering, potential empty results, or authentication requirements, which are common behavioral considerations.

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, front-loaded sentence with no redundancy. It packs the resource, search fields, and return type into a compact statement, earning every word.

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?

For a simple one-parameter search tool with no output schema, the description adequately covers purpose, inputs, and return types. It could note result pagination or ordering, but given the low complexity, this is not a critical gap.

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 coverage is 100% with a basic description and example. The tool description adds meaning by specifying the query can be a name, brand, note, or perfumer, and supports both Latin and Cyrillic scripts, enriching the parameter's context beyond the schema.

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 searches the parfica.com fragrance encyclopedia by name, brand, note, or perfumer, and returns matching entities. It is specific with a verb and resource, but does not explicitly differentiate from sibling tools like find_dupes or fragrance_info.

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?

No guidance is given on when to use this tool versus alternatives (find_dupes, fragrance_info). There are no exclusions, prerequisites, or usage scenarios, leaving the agent to infer context from the tool name.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.