Docket Nexus

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so safety is covered. The description adds useful behavioral context by scoping to public cases, noting fields are 'as shown on the case page,' and qualifying disposition as 'when recorded.' This goes beyond the structured annotations without contradicting them.

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 that immediately states the action and input, then compactly lists the returned fields. Every part earns its place, and there is no filler or redundant qualification.

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 read-only tool with no output schema, the description is complete: it specifies the input format, the source of the data, and the full set of returned fields, including the conditional disposition. The annotations cover safety and idempotency, so nothing critical 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 description coverage is 100% and the single case_url parameter already includes a full example and notes that it is returned as canonical_url by search_cases and get_company_cases. The tool description restates the URL requirement but adds no new parameter semantics beyond what the schema provides.

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 and resource: 'Get a public case by its Docket Nexus URL.' It also enumerates the exact fields returned (caption, court, docket number, dates, judge, cause, nature of suit, parties, disposition), which clearly distinguishes this case-detail tool from siblings like get_case_docket and search_cases.

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 makes the intended usage context clear: call this when you already have a Docket Nexus case URL and want the case summary page data. It does not explicitly name alternatives or exclusions, but the URL-based precondition and field list are sufficient directional guidance.

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?

The description goes well beyond the annotations by disclosing ordering (newest first), pagination via next_cursor, the 50-item cap, document availability, and the fact that unpublished entries are omitted but counted. This gives an agent a realistic behavioral model before calling.

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 short sentences, each carrying distinct information: what is listed, how pagination works, and how unpublished entries are handled. It is front-loaded with the most important purpose and has no filler.

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 description covers purpose, ordering, pagination, limit, and filtering behavior. Since there is no output schema, it would be stronger if it briefly described the shape of a docket entry or how 'document availability' appears in results, but it is still sufficient for an agent to invoke the tool confidently.

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%, so the baseline is 3. The description reinforces cursor usage and the 50-item limit, but these details are already present in the schema. It does not add meaningfully new semantics for case_url or the cursor format beyond what the schema provides.

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?

Description begins with a specific verb and resource: 'List a public case's docket entries newest first.' It adds order and document-availability scope, which clearly distinguishes this from siblings like get_case or get_document. The public-case qualifier also prevents confusion with private or internal tools.

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 clear context for use: retrieving docket entries for a public case. It also implies limitations ('public case') but does not explicitly name alternative tools or state when NOT to use this one. It lacks direct sibling differentiation, but the intended use case is obvious.

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 mark the tool as read-only, idempotent, and non-destructive, so the description does not need to restate safety. It adds useful behavioral specifics: the returned fields, the conditional verified-roster identity, and an illustrative slug format. Pagination or error behavior is not covered, but for a simple profile read 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?

A single, front-loaded sentence with a clean colon-delimited list and one parenthetical example. Every element earns its place, with no filler or redundant restatement of the tool name.

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 definition is largely complete for a one-parameter read-only lookup: the schema documents the input, annotations cover safety, and the description lists the expected output fields. It could mention not-found or roster-exclusion behavior, but that is a minor gap given the tool's simplicity.

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 input schema has 100% documented coverage for the single slug parameter, including format, examples, and source URL. The description reuses the slug concept and gives a different example, but adds little beyond what the schema already provides, so the baseline 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 opens with a specific action ('Get a public company's Docket Nexus profile'), identifies the key input (slug), and enumerates the profile contents. This clearly distinguishes it from siblings like get_company_cases and search_cases, which target case lists rather than a single company profile.

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 an unambiguous use case: retrieve a company-level profile by slug when you need company identity, linked case count, or top case types/courts. It does not explicitly name alternatives or state when not to use it, so it falls short of a 5, but the context is clear.

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 non-destructive behavior. The description adds meaningful behavioral constraints: only public cases, sorting order, optional filters, pagination via next_cursor, and a maximum of 25 results per 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?

Two sentences with no wasted words. The core purpose is front-loaded, followed by filtering, sorting, and pagination constraints, all essential for correct invocation.

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 description covers purpose, filters, sorting, pagination, and result limits. Since there is no output schema, it could ideally describe the shape of returned case items, but the sibling get_case tool and the phrase 'List public cases' make the usage reasonably complete.

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 schema already documents all six parameters. The description summarizes sort, court/nature_of_suit filters, cursor, and limit, but adds no meaning beyond what the schema provides.

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 and resource: 'List public cases linked to a company.' It also adds sorting, filtering, and pagination details that clearly distinguish it from siblings like get_company, get_case, and search_cases.

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 makes clear when to use it: when you need public cases for a specific company slug, with optional filters and pagination. It does not explicitly name alternatives or state when not to use it, so it stops short of a 5.

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?

The description adds value beyond annotations: it explicitly states that only metadata is returned and 'no document text' is served. This prevents an agent from expecting the document content, which is a behavioral trait not captured by the readOnlyHint or idempotentHint annotations. Annotations provide the safety profile, but the description adds the return-scope constraint.

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 concise sentences, each earning its place. The first states the purpose and the resource, the second explicitly limits the output to metadata. No fluff, no repetition of schema info. It is front-loaded with the core action and resource.

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 simple with a single parameter, fully described in the schema, and the description clarifies the metadata-only scope. With annotations covering safety and idempotency, and no output schema to explain, nothing critical is missing. It could benefit from mentioning the output format (e.g., JSON), but that is not essential for a metadata-only read operation.

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 has 100% coverage with a description for document_id, so the baseline is 3. The description adds crucial context: it explains the document_id comes from a get_case_docket entry's document_id field, which the agent might not know from the schema alone, and reaffirms that only metadata is returned. This enhances the parameter 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?

The description states a specific verb ('get'), a clear resource ('docket document'), and the identifying field ('by its Docket Nexus document id'). It lists the types of metadata returned, which distinguishes it from sibling tools that handle cases or companies. It clearly differentiates itself from get_case_docket (which retrieves an entry list) by focusing on a single document's metadata.

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 it is used when you have a document_id from a docket entry, as the parameter description says 'as returned in a get_case_docket entry's document_id field'. It does not explicitly state when not to use it, but the focus on a single document and metadata-only makes that clear. No alternatives are named, but the context makes the use case apparent.

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 mark the operation as read-only and idempotent, and the description adds meaningful behavioral details: results are newest first, capped at 25 per call, pagination uses next_cursor, and invalid docket number formats are refused. This goes well beyond the schema and annotations.

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 carry all the essential information: accepted query forms, a concrete example, result ordering, pagination limit, and cursor usage. No wasted words, and the most important constraint is front-loaded.

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 description, together with the fully documented schema, covers everything needed to call the tool: query syntax, limit semantics, cursor usage, and pagination behavior. There is no output schema, and the return shape is not described, but the mention of next_cursor provides enough context for a search tool.

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%, so the baseline is 3. The description goes further by explaining the query format with an example, clarifying the docket-number-office-prefix requirement, and tying cursor to next_cursor for pagination. This adds practical value beyond the schema's own parameter descriptions.

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 public cases by specific query types: caption words, 'A v. B', or a federal docket number with office prefix. It gives a concrete example and is distinct from sibling tools like get_case, though it does not explicitly name or contrast them.

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 explains what queries are accepted and that docket numbers without office prefixes are refused, but it provides no guidance on when to choose this tool over alternatives like get_case or get_case_docket. Sibling differentiation is absent.

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