Anthid

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

With no annotations, the description carries the full burden. It transparently discloses what the tool returns and the three accepted input formats, but it does not explicitly state that the operation is read-only, has no side effects, or how it behaves for unknown endpoints. The 'Return' wording implies a safe lookup but stops short of full disclosure.

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 concise sentences front-load the core output and purpose, then give usage context, then enumerate accepted input forms. Every sentence carries information, and there is no redundancy with the title or schema.

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 there is no output schema, the description compensates by detailing exactly what the reference will contain: authentication, parameters with examples, request body schema and examples, and response examples. It also clarifies the optional method parameter's role and gives accessible input examples, making the tool fully callable.

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's examples ('/v1/orders', 'POST /v1/intents', 'submitIntent') add practical format clarity beyond the schema, but they do not meaningfully expand on the endpoint and method semantics already described in the input 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 uses a specific verb ('Return') with a clear resource ('the full reference for one endpoint') and enumerates the exact contents, distinguishing it from sibling tools that list endpoints or search the API. The title and description align without tautology.

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 explicitly tells the agent when to use the tool: 'Read this before writing a request rather than inferring the shape.' However, it does not name alternatives or state when NOT to use it versus siblings like get_anthid_api_schema or search_anthid_api, so some exclusion guidance is missing.

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 burden. It discloses that references are expanded and that it returns a single schema, which is useful behavioral context. However, it does not mention potential error conditions, authentication requirements, or whether the operation is safe (read-only). For a simple get operation, this is acceptable but not rich.

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 filler. The purpose and usage are front-loaded, and the examples are integrated naturally. Every word earns its place, making it efficient and easy to parse.

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 tool with one parameter, no output schema, and a straightforward purpose, the description is complete. It explains what it returns (a schema with references expanded), when to use it, and how to specify the name. No additional information is needed for an agent to call it correctly.

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 already covers the parameter (name) at 100% coverage, so the baseline is 3. The tool description adds concrete example schema names ('SubmitIntentParams' or 'OrdersResponse') and specifies that the name should match how it appears in endpoint descriptions, going beyond the schema to clarify valid values.

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 it returns a named schema from the API reference, with a specific verb 'Return' and resource 'named schema'. It distinguishes from siblings like describe_anthid_endpoint (endpoints) and list_anthid_endpoints (lists) by focusing on schema retrieval, making the purpose unmistakable.

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 explicitly states when to use it: 'Use this when an endpoint description names a schema you need in full.' This gives a clear condition for use, though it does not mention when not to use it or alternative tools. The condition is specific enough to guide selection.

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 clearly states the tool returns the positioning overview and enumerates its content, which is more than a simple 'Get overview'. It does not disclose potential errors, authentication, or response format, but for a read-only, parameterless 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?

Two sentences, front-loaded with purpose and content, followed by usage guidance. No waste or redundancy.

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, parameterless read tool with no output schema, the description fully covers what it returns and when to use it. No missing information an agent needs to call it correctly.

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 are no parameters; the schema has no properties. Per the baseline for 0 parameters, the description does not need to add parameter information, and it does not. The baseline of 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 states a clear verb ('Return'), a specific resource ('positioning overview for Anthid'), and enumerates its content (what the platform does, what it replaces, who it is for, and implementation detail). It also differentiates from search tools by advising to use it before reaching for a search, though it does not name sibling tools 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?

It explicitly advises using this tool to answer 'what is Anthid' before reaching for a search, giving a clear when-to-use condition. It does not explicitly mention when not to use it or name alternatives, but the guidance is clear enough to route the agent appropriately.

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 provided, so description carries full burden. It discloses the grouping and content but doesn't mention pagination, error handling, or auth requirements. It's a simple read operation but lacks behavioral details.

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, front-loaded with the main action and content, second sentence gives usage context. No redundant information.

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 listing tool with one optional parameter and no output schema, the description is sufficient. It covers purpose, usage, and parameter context. Could mention when to use describe_anthid_endpoint instead, but not critical.

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 the 'service' parameter. The description adds context that it's for filtering by group but doesn't add syntax or format details beyond schema. 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?

States specific verb 'list', resource 'endpoints', and details 'grouped by service, with its method, path, and summary'. Clearly distinguishes from siblings like search_anthid_api and describe_anthid_endpoint by specifying exhaustive listing vs searching or describing.

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?

Explicitly says 'Use this to see the shape of the API before searching it', providing a clear context. However, it doesn't explicitly mention alternatives or when not to use, so not 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?

With no annotations, the description carries the full burden. It transparently states the operation is a read-only listing of public pages and specifies the output shape. It does not mention pagination or volume limits, but for a zero-parameter list tool the core behavior is well disclosed.

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: the first states the action and output, the second gives the intended use case. 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?

For a simple, zero-parameter, no-output-schema tool, the description is nearly complete: it covers scope, output fields, and a concrete use case. Minor omissions like pagination behavior or an explicit pointer to search_anthid_site for targeted lookups are acceptable here.

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, so there is nothing for the description to clarify beyond the schema. The description appropriately focuses on what is returned rather than inputs.

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 ('List'), a precise resource ('every public page on anthid.com'), and the returned fields (title, description, URL). It is clearly distinct from sibling tools like list_anthid_endpoints, which concern API endpoints rather than site pages.

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 use case: 'Use this to find the right page to cite or to fetch.' This tells the agent when to choose the tool, though it does not explicitly mention alternatives like search_anthid_site or state when not to use 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?

With no annotations provided, the description carries the behavioral disclosure burden. It clearly conveys that this is a read-only search operation and specifies the return fields (method, path, summary). It does not discuss edge cases like no matches or matching semantics, but nothing about the tool suggests destructive or surprising behavior.

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 filler. The primary purpose and output are stated first, followed by concrete usage examples and the relevant follow-up tool. Every sentence 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 search tool, the description is complete: it says what to search, what results contain, how to phrase queries, and what to do next. Parameter details are fully covered by the schema, and the return shape is described in prose.

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 adds useful meaning beyond the schema by giving natural-language examples of what query should contain ('submit an order', 'list positions', 'set a risk control') and clarifying that the query describes the desired endpoint behavior rather than a literal search string.

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 action ('Search the Anthid REST API reference') and states exactly what it returns ('matching endpoints with their method, path, and summary'). It is clearly distinct from sibling tools like describe_anthid_endpoint, which is explicitly positioned as the follow-up for parameter 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 explicitly tells the agent when to use this tool ('Use this to find which endpoint does something') and directs it to describe_anthid_endpoint after a match. It does not, however, contrast this tool with other sibling search/browse tools such as search_anthid_site or list_anthid_endpoints, so exclusion guidance is incomplete.

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 burden of behavioral disclosure. It discloses the return behavior ('matching excerpts with their URLs') and the scope of the search. It does not mention auth, rate limits, or explicit non-mutating guarantees, but a search tool's read-only nature is strongly implied, so the gap is less critical than for a mutation 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?

Three sentences, each earning its place: the first defines the core action and return format, the second lists concrete use cases, and the third routes to relevant alternatives. It is front-loaded with the most critical information and contains 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?

With a two-parameter schema, no output schema, and no annotations, the description covers everything an agent needs: what is searched, what is returned, when to use it, and which alternatives exist. It even notes the external docs server for content the current corpus lacks. Nothing essential 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%, so the baseline is 3. The description adds value beyond the schema by providing concrete query examples ('pricing free tier', 'which brokers') and clarifying the intended use cases for the query parameter. This helps the agent formulate effective queries, making it a step above the baseline.

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 ('Search'), the resource (anthid.com's product, pricing, and company pages), and the output ('matching excerpts with their URLs'). It also distinguishes itself from siblings by naming search_anthid_api and describe_anthid_endpoint as the API-focused alternatives. This is unambiguous and sets it apart from sibling 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 explicitly says when to use this tool: 'questions about what Anthid is, what it costs, which brokers it connects, or how to get in touch.' It also gives clear exclusions — API introspection tools for endpoints/parameters, and an external MCP server for narrative guides. This offers complete routing guidance without leaving anything to inference.

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