Action Battery Wholesalers product catalogue

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

Annotations already declare readOnlyHint, idempotentHint and openWorldHint=false, so safety is covered. The description goes beyond that by disclosing conditional return behavior: a discharge table yields figures only after datasheet verification, otherwise just the link and page. That is real behavioral context the annotations cannot express, though the condition itself is phrased vaguely.

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 short sentences, front-loaded with the core purpose. The second sentence about discharge tables is somewhat cryptic but does not pad the description.

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 output schema, the description must carry the return-value burden, and it does so only partially: it hints at 'link and page' versus figures for discharge tables, but never clarifies what 'full text' means for a product series or how the non-discharge case is shaped. Adequate but leaves an agent guessing at 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?

There is a single parameter with 100% schema description coverage, so the schema already explains that id comes from search, find_series or get_documents. The description adds only the notion that exactly one result is read, which is a marginal restatement rather than new semantics.

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: 'Read the full text of one result from search', and enumerates the item types it covers (web page, PDF, product series). It clearly separates itself from search by being single-result retrieval, though it doesn't explicitly contrast with get_documents or find_series, which also produce ids.

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?

Usage is implied by 'one result from search' — fetch comes after search. There is no explicit statement of when to prefer this tool over get_documents, find_series, or search, and no prerequisites or exclusions are given.

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?

Annotations already declare that the tool is read-only, idempotent, non-destructive, and closed-world. The description adds useful context that results include each series' product page and documents, but it does not describe pagination, result limits, or default behavior when no filters are provided.

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 two sentences and front-loads the core purpose and filters. The second sentence efficiently covers the return payload, with no wasted prose.

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 read-only lookup tool with fully documented parameters and no output schema, the description gives adequate context about filters and returned content. It could be more complete by explaining result limits, pagination, or the behavior of an empty query.

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%, so the parameters are already well documented. The description reinforces example values for chemistry, voltage, and application but does not add syntax or behavior 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 names a specific verb and resource: find a stationary battery or product series offered by Action Battery Wholesalers. It clearly scopes the lookup by chemistry, voltage, and application, but does not explicitly distinguish this from the sibling `search` tool.

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?

Usage is implied by the listed filter dimensions, so an agent can infer that this tool is for attribute-based series lookup. However, there is no explicit when-to-use/when-not-to-use guidance and no comparison to `search` or `fetch`.

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?

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so safety is covered. The description adds one genuinely useful behavioral fact: third-party documents are not hosted but linked at their source. It says nothing about result size, ordering, or pagination.

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 tight sentences with the resource and both scoping modes front-loaded. The type enumeration largely duplicates the enum in the schema, which costs a little space for little gain.

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 two-optional-parameter list tool with no output schema, the description covers what the tool returns at a high level (document links, third-party at source) but leaves the no-argument 'list everything' behavior and result shape unstated.

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 50% (only 'series' is documented), so the description must compensate. It conveys the meaningful semantic that the two filters are optional and combinable ('across the site' = type only), which is real added value, but it omits the 'other' enum value and never states what happens when both parameters are omitted.

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?

Specific verb ('List') and resource ('documents') with the publisher named and the two scoping modes spelled out ('for a series, or of one type across the site'). It never names a sibling tool, so differentiation from search/find_series is left implicit.

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 'for a series, or of one type' phrasing implies the two ways to call it, but there is no explicit when-to-use guidance, no exclusions, and no pointer to alternatives (e.g., use search for keyword queries, find_series to obtain the series id).

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?

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so the safety profile is covered. The description adds genuinely new behavioral context: 'It sends nothing; the customer sends the request themselves,' which preempts the common misreading that this tool submits a quote request. It stops short of describing the response format or any limits.

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 tight sentences with zero filler; the core capability and the return content are front-loaded, and the critical 'sends nothing' caveat closes it. Every clause 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 zero-required-parameter, read-only informational tool with no output schema, the description adequately covers what comes back (address plus required details) and confirms no side effects occur. Minor gaps remain around the exact shape of the returned guidance, but nothing prevents a correct invocation.

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?

Both optional parameters (series, application) are fully documented in the schema at 100% coverage, so the schema carries the load. The description gestures at 'what to include' but never explains what the parameters do with that input or whether supplying them changes the returned guidance, adding little 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 states concretely what the tool returns: the address to write to and a checklist of what to include in a quote request. It is not a tautology of the name, but it never contrasts itself with siblings like fetch, search, or sizing_tool, so the agent must infer that this is the informational 'how to get a quote' resource rather than an actual quote-submission action.

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?

Usage is implied rather than stated: 'How to ask ... for a quote or price' suggests calling it when a customer wants pricing, and 'so the engineers can answer without a round of questions' hints at the goal. There is no explicit when-not, no named alternative (e.g. sizing_tool for selecting a battery), and no prerequisites, leaving the agent to infer routing.

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?

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds the useful disclosure of return shape (ids, titles, source links) and warns that results are references, not full documents. It does not mention pagination or result-count limits, so not a 5.

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?

Three tight sentences: capability first, query style second, return shape and next step last. The examples and the fetch hand-off both earn their space.

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 single-parameter search tool with no output schema, the description covers everything an agent needs: what is searched, how to phrase the query, what comes back, and what to do next. Nothing material is missing.

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% and there is only one string parameter, so the baseline is already met. The description still adds value by demonstrating the expected natural-language query form with concrete examples ('12 V gel battery for solar', 'OPzS 2V cell SDS'), which the terse schema does not.

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?

Specific verb (Search) plus named resource (Action Battery Wholesalers site) and an explicit enumeration of what is indexed: product pages, datasheets, discharge tables, manuals, SDS, technical articles. This clearly separates it from fetch, which reads a single result.

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?

Tells the agent how to phrase input ('Ask in plain words') with two concrete example queries, and explicitly routes the follow-up step: 'read one with fetch.' Both the invocation style and the alternative tool are named.

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?

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds genuinely useful context beyond that: it warns that no sizing is performed online and that this connector does not compute a result, which prevents an agent from treating output as a sizing answer. It does not describe the shape of the returned guidance.

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 short sentences with the most important fact — that this is not a sizing engine — front-loaded. Mild redundancy between 'NO online sizing tool' and 'cannot size a system', but each sentence still 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 zero-parameter, read-only informational tool with no output schema and full annotation coverage, this covers what an agent needs: what the tool is not, what it returns, and the next step. The only gap is the absence of an explicit hand-off to the 'quote_request' sibling by name.

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 and the schema carries no burden. The description helpfully lists the three inputs the customer must supply to the engineers (load, runtime, voltage), which is extra semantic value even though those are not tool parameters.

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 states plainly that this is an informational/instructions tool and explicitly negates the expectation set by the name 'sizing_tool' — it says the connector cannot size a system. It then describes the actual content (the process for getting a system sized). It is clear, though it never quite says 'this tool returns guidance rather than results' in a single direct phrase.

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 establishes the trigger condition (a customer needs a system sized) and routes the agent to the correct path — sending load, runtime and voltage with a quote request, which maps to the sibling 'quote_request'. It does not name the sibling tool explicitly or state when not to call this tool, so it is strong but not exhaustive.

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