RecallRadar

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

Annotations already declare readOnlyHint=true, and the description stays fully consistent — 'created or updated' describes the rows, not a mutation the tool performs. It adds genuinely non-obvious behavioral context the annotations do not carry: the Authorization/Bearer and x402 payment requirements, the fixed-price-per-call model, and the authoritative-source caution. This is exactly the kind of supplementary behavior disclosure the rubric asks for.

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 definition has no fluff: behavior, ordering, pagination handshake, payment, and data provenance each earn their sentence and appear in logical order. The final pair of clauses ('The official agency notice is the authoritative source' and 'source_url is authoritative') slightly repeats the same idea. At roughly 100 words it is dense but scannable rather than bloated.

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 10-parameter, read-only tool with no output schema, the description carries the weight of the non-obvious details: ordering, the change-type field, the pagination token, payment mechanics, and source reliability caveats. The schema fills in the filter semantics, so the combination covers what an agent needs for correct invocations. It does not sketch the full row shape, but with eight named parameters and this behavioral detail, the gaps are acceptable.

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 80%, so the schema carries most parameter meaning and the baseline is 3. The description surfaces the payment out-of-band metadata slot (params._meta["x402/payment"]) and the meta cursor contract, which do add information beyond the schema. It does not elaborate on the filter parameters' behavior beyond what the schema already says.

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 opens with a specific verb + resource: 'Recalls created or updated after a timestamp, oldest change first', which crisply states what the tool returns and how it is ordered. The 'change = created | updated' detail makes it easy to tell this apart from search_recalls (query-based) and get_recall (single record) without opening schemas. It stops short of explicitly naming the siblings it differs from, so differentiation is implied rather than stated.

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 gives a direct usage pattern for the core flow: 'Pass meta.until as the next since', which tells an agent exactly how to paginate and loop a sync of changed records. It also provides the payment/authorization procedure, which is essential for successfully invoking this tool. However, it never says when to choose diff_since over search_recalls or get_recall, leaving that selection 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?

Goes beyond annotations by disclosing that the operation is paid (price per call), returns raw agency payload and status history, and that the official source is authoritative. This is richer than the readOnlyHint and provides actionable behavioral context.

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?

Description is moderately long but each sentence adds value: payment, data sources, caution. It front-loads the core purpose and includes necessary operational details; only minor trim possible without losing substance.

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 single-parameter tool with no output schema, the description covers payment, return contents, and source authority. It omits potential error cases or rate limits, but these are less critical given the tool's specificity and read-only nature.

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 already describes the parameter as '32-hex recall id or page slug' (100% coverage). The description repeats this but adds the clarification that it can be either id or slug, which is slightly redundant. It doesn't add format details beyond the schema, so baseline 3 is appropriate.

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 a specific verb ('Get') and resource ('one recall') with clear selection criteria ('by id or slug'). It distinguishes from siblings like search_recalls (bulk/search) and list_agencies (list) by focusing on single-item retrieval with raw payload and history.

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?

Provides explicit payment requirements (Bearer token or x402) and a caution to confirm details at the source, indicating when to use it (single recall lookup). It doesn't explicitly list alternatives or when not to use, but the single vs. search contrast is implied through the sibling tool names.

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=true, and the description adds useful context beyond that: the tool is free, indexes public FDA/USDA/CPSC notices, and the official agency notice is authoritative with a confirmation caveat. It does not describe the exact return format, but for a read-only listing tool the added source and authority context is valuable.

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 short and front-loaded with the core purpose, followed by useful source and authority context. The word 'Free' is somewhat filler but not harmful, and the overall structure is compact and readable.

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 no-argument listing tool with read-only annotations, the description covers the main need: what is listed, which agencies are indexed, and a reliability caveat. It is slightly light on exact output structure, but the absence of parameters and output schema keeps the gap minor.

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 has zero parameters and the schema coverage is effectively 100%, so there are no parameter semantics for the description to clarify. Baseline for zero-parameter tools is 4, and the description adds no conflicting or missing parameter information.

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 title and first sentence make clear this tool lists the agencies RecallRadar indexes along with their labels, and the named agencies (FDA, USDA FSIS, CPSC) distinguish it from recall/search/diff siblings. However, the description's first sentence is a noun phrase rather than an explicit verb+resource statement, so it leans on the title for the verb.

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 guidance on when to use this tool versus alternatives such as search_recalls or get_recall. The description offers general context about RecallRadar's data sources but no conditions, exclusions, or routing hints.

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?

Beyond readOnlyHint=true, it discloses important behaviors: results are newest-first, calls are priced per row, payment can be sent via bearer token or x402, and the source notice is authoritative. It also adds a safety directive to confirm details at the linked source before acting.

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 front-loaded with the main purpose, then payment and authoritative-source caveats. It is reasonably tight, though the authoritative-source point is repeated in three consecutive sentences.

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 11 optional parameters and no output schema, the description provides enough context for an agent to invoke it correctly: agencies, search axes, ordering, payment, and authoritative-source guidance are all present. It does not describe the full response shape, but that is a smaller gap given the rich filter documentation.

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 schema description coverage is 82%, so the structured schema already documents most parameters. The description adds only light semantic value by summarizing filter axes, though it does clarify that source_url is authoritative and that limit affects pricing.

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 ('Search FDA, USDA FSIS, and CPSC recalls'), lists concrete filters, and is clearly distinct from siblings like get_recall or list_agencies. It is unambiguous about what kind of lookup this is.

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 conveys a clear use case: searching across multiple consumer product/food recall sources with rich filtering. It does not explicitly say 'use get_recall for a single known recall', but the search-focused wording is enough to route agent selection away from the siblings.

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