Lavenders (LAVNDR120)

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

No annotations exist, so the description carries the full burden; it does disclose a genuine behavioral trait beyond structure — that the returned content constrains how answers must be phrased. However, it says nothing about the read-only nature, size/format of the payload, or whether the rules are mandatory preconditions for every other tool call.

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?

A single front-loaded sentence with no filler, and the brand identifier LAVNDR120 is surfaced immediately. It is efficient but so terse that the 'rules' component is never unpacked.

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?

With no parameters and no output schema, the description need not document returns, so the bar is low. Still, for a zero-arg grounding tool the agent is left unclear on what the payload actually contains and whether calling it is a prerequisite for the package/FAQ tools.

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?

The tool takes zero parameters, so there is nothing for the description to disambiguate; the empty schema fully covers the input surface. Baseline 4 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 conveys the resource ('What Lavenders (LAVNDR120) is') plus an extra payload (answer rules), but it is phrased as a noun clause rather than a verb+resource statement, and it never contrasts itself with get_faq, get_live_index, get_package or list_packages. An agent can guess this is brand grounding content, but the boundary with the sibling FAQ tool is left to inference.

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?

There is no statement of when to call this versus the sibling tools, no indication that it should be called first as grounding, and no exclusions. The phrase 'rules any answer must respect' hints at usage but never tells the agent under what conditions to invoke it.

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?

No annotations are present, so the description carries the full burden. It doesn't say whether this is a static/snapshot read, how content is versioned, or what form the answer takes. The only disclosure is content scope ('includes what the platform does not offer'), which is a minor positive.

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?

It is short and there is no filler, but it is a fragmented noun phrase rather than a front-loaded statement of function. Brevity here reflects under-specification more than tight editing.

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 zero-parameter lookup with no output schema, the minimum an agent needs is what content comes back, and the description does signal FAQ content including platform limitations. It stops short of describing structure or freshness, but the tool's low complexity limits the cost of that 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?

The tool takes zero parameters, so there is nothing for the description to clarify. Baseline 4 applies; no semantic gaps are possible.

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 expands the tool name into a noun phrase — 'Frequently asked questions' — without a verb or resource framing. The added clause about covering what the platform does not offer gives a small scope hint, but an agent gets no clearer picture than it did from the name 'get_faq'.

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?

It provides no indication of when to call this rather than siblings such as get_brand_overview, get_live_index, or get_package. The FAQ content overlaps conceptually with a brand overview or package info, so routing guidance was particularly needed here and is absent.

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 present, the description carries the full disclosure burden. It usefully flags the tool as informational (no side effects) and names the returned fields, but says nothing about data freshness, caching, or failure behavior for what is presumably a live quote endpoint.

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 compact fragments with the resource and payload front-loaded and no filler. The parenthetical is efficient; the only cost is slight terseness that leaves behavioral detail unstated.

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?

It is a simple zero-parameter read with no output schema, so the description must convey the return shape — it does, naming NAV and day change. Missing only freshness/latency context, which is minor for a read-only getter.

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?

The tool takes zero parameters, so the baseline is 4. The description correctly implies a parameterless call and adds no misleading parameter claims.

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 specific resource (the LAVNDR120 index card) and names the payload (net asset value and day change), so an agent knows exactly what it retrieves. It does not explicitly contrast itself with siblings like get_brand_overview or get_package, but the subject matter is distinct enough to be told apart.

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?

"Informational only" implies this is a read for reference rather than an input to a transaction, which gives some usage signal. However, it never names when to pick this over get_brand_overview or other siblings, nor does it state any preconditions, leaving routing to inference.

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?

No annotations are provided, so the description carries the full behavioral burden, and it says nothing about what happens on an invalid id, whether the call errors or returns empty, or what a package record contains. Listing the valid ids is the only behavioral content and it merely restates the schema.

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?

A single front-loaded sentence with no filler. The enumerated values, however, are redundant with the schema and consume most of the sentence's length.

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?

The tool is trivial (one enum parameter, no nesting) and no output schema exists, so the description should say something about what a package record returns or how the distinct package types differ. It is minimally sufficient to invoke, but leaves the agent guessing about the response.

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 0%, but the single parameter is a fully enumerated required string, so there is little semantic ambiguity to resolve. The description repeats the seven allowed values without adding meaning such as whether ids are case-sensitive or how they map to packages.

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 specific verb and resource: fetch one package by its id, which implicitly distinguishes it from the list-style sibling list_packages. The enumerated id values sharpen what 'package' means, though they duplicate the schema and the tool never names its sibling explicitly.

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?

There is no statement of when to use this versus list_packages or get_brand_overview, and no prerequisites or error conditions. The word 'One' weakly implies single-item retrieval, but an agent must infer the routing decision entirely on its own.

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 burden; it does disclose what content comes back (seven packages with prices and seats), which is useful. However, it says nothing about auth requirements, rate limits, or that this is a read-only catalog dump.

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?

A single fragment sentence with no filler, front-loading the resource and the fields returned. The lack of a leading verb keeps it from being a fully polished 5.

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 zero-param listing with no output schema, the description adequately states the item count and key fields. It stops short of describing the full record structure or ordering, which would matter given there is no output schema to fall back on.

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?

The tool takes zero parameters, so there is nothing for the description to disambiguate. The baseline of 4 applies for a parameterless operation.

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 names the exact resource being returned (the seven named packages) and the key fields (prices and seats), making it clear this is a full listing. It doesn't use a verb and doesn't explicitly contrast with get_package, but the plural 'seven packages' inherently distinguishes it from the singular sibling.

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?

There is no explicit when-to-use statement and no reference to alternatives like get_package for a single package. An agent must infer that this returns the whole catalog rather than one item.

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