apis-io

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

With no annotations, the description carries full responsibility for disclosing side effects, but it only says 'Add' without explaining whether entries are appended, deduplicated, or what happens if the list does not exist. Ownership and authorization requirements are also not addressed.

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, efficient sentence with no filler, but it is extremely terse and could include a few more details without losing conciseness. The 'PRO —' prefix is harmless but adds no value.

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 mutation tool with no annotations and no output schema, the description is incomplete. It fails to explain the role of 'id', the acceptable values for 'members', and what the tool returns or changes upon success, making it difficult for an agent to use correctly without additional information.

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 0%, so the description must explain the parameters. It mentions 'providers/APIs (by slug or aid)' which maps to 'members', but it does not clarify that 'id' refers to the list identifier, nor does it specify whether members should be slugs, aids, or a mixture of both.

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 action ('Add providers/APIs') and the target ('one of your lists'), distinguishing it from sibling tools like create_list, get_list, and delete_list by focusing on the add operation.

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?

No guidance is provided on when to use this tool versus alternatives, nor on prerequisites such as list existence or how to obtain the list id. The description does not mention create_list as a related alternative for creating new lists.

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 full behavioral disclosure burden. It effectively communicates the federated/overview nature, the per-section limit, and the counting behavior. It does not, however, explicitly mention whether the tool is read-only or safe, or how filters combine (e.g., any vs all), but those are less critical for a search tool and the description does not contradict its intent.

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, front-loaded with the imperative 'START HERE.' Every sentence adds value: the first explains what the tool returns and the second gives usage differentiation and parameter notes. There is no fluff or repetition.

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 the tool's complexity (12 optional parameters, no output schema, no annotations), the description provides a solid functional overview: what it returns, that it's a federated summary, the per-section limit, and pointers to alternatives for deeper dives. It does not explain the exact response structure or default behavior without a query, but the schema's sort description partially covers the default. Overall, it is sufficient for an agent to correctly select and invoke the tool in most cases.

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 covers only 42% of parameters with descriptions; the description adds meaning by listing filter dimensions (tags, artifact types, industry, region, rating band) and clarifying that 'limit' applies per section. However, it omits several parameters like 'q', 'area', 'providers', and 'min_score', leaving gaps. The schema's descriptions for 'sort', 'band', 'match', and 'tags' already help, but the description does not fully compensate for missing coverage on all 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 clearly states it provides a 'Federated overview of the APIs.io catalog for a query' returning 'the top matching APIs, providers, AND tags in one call, each with its total match count.' This specific verb+resource+scope immediately distinguishes it from siblings like find_apis, get_api, and find_tags, which are explicitly mentioned as alternatives for other use 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 is explicit about when to use this tool: 'START HERE.' It also provides clear guidance on alternatives: 'To page/sort the full list of ONE type, use find_apis / find_providers / find_tags; for one entity, get_api / get_provider.' This directly addresses both when to use and when not to use, with named sibling tools.

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?

Since no annotations are provided, the description carries the full burden of behavioral disclosure. It only describes semantic output and includes an unexplained 'Pro.' tag, without stating whether the operation is read-only, what the response looks like, or any access restrictions.

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 concise sentence with no filler, making it efficiently structured. However, the trailing 'Pro.' is an unexplained fragment that slightly reduces clarity.

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 tool with no output schema or annotations, the description provides almost no operational context: no return format, usage notes, or relationship to sibling tools. This is inadequate for an agent to correctly invoke and interpret the 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?

The schema has one required parameter 'slug' with 0% description coverage, and the tool description does not mention the parameter. The phrase 'A company's' implies the slug refers to a company, but no format, examples, or value constraints are provided, so the description barely compensates for the schema gap.

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 defines the output as a company's weakest investment dimensions, which gives some semantic content beyond the name, but it lacks an explicit verb or action. It does not clearly distinguish this tool from sibling tools like gap_analysis or industry_gap_analysis.

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 guidance on when to use this tool versus alternatives such as gap_analysis or find_company_insights. The trailing 'Pro.' hint is ambiguous and does not clarify tool selection or integration context.

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 the output composition (composite/band, per-facet leaders, artifact-coverage matrix), which is useful behavioral context. The read-only nature of 'compare' is implied, and no side effects are mentioned. More detail on output format would be beneficial but is not critical for this simple 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?

Comprises a single, information-dense sentence. Front-loads the action and resource, then lists output specifics. No wasted words; every component adds value.

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 one simple parameter and no output schema, the description gives a clear summary of the tool's purpose and output dimensions. It could explain terms like 'composite/band' or 'per-facet leaders' in more detail, but the overall behavior is communicated adequately for an agent to select and invoke 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?

Schema coverage is 100% for the only parameter ('providers' as array of strings), and the schema already describes it as 'Provider slugs to compare (2+).' The description adds 'side by side' and reiterates '2+', but provides no meaningful extra parameter-level detail beyond the schema. 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 uses a specific verb ('Compare') with a clear resource ('providers') and scope ('2+ providers side by side'). It also lists specific output dimensions (composite/band, per-facet leaders, artifact-coverage matrix), distinguishing it from sibling tools like get_provider or find_providers.

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?

States '2+ providers' as a clear usage condition, implying this is for multi-provider comparison. Does not explicitly mention alternatives or exclusions, but the context is obvious given sibling names. No when-not-to-use guidance is missing that would be critical.

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 burden. It discloses persistence, ownership, and the API-key requirement, but doesn't mention what the operation returns or whether names must be unique. This is partial 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?

Two short sentences, front-loaded with the verb and object. No redundant language.

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 two-parameter creation tool, the description covers the essential prerequisites (PRO, API key) and behavior (persistent list). It doesn't explain return values, but the lack of an output schema makes that less 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 coverage is 50%, with 'members' described in the schema and 'name' left undocumented. The description reinforces 'named' and 'of providers or APIs' but doesn't explicitly define the members parameter's format beyond what the schema 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?

Description uses specific verb 'Create' and identifies the resource as 'a named, persistent list' of 'providers or APIs.' This clearly differentiates from siblings like add_to_list and delete_list, which operate on existing lists.

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 clear context: creates a new, named persistent list and notes the PRO/API-key prerequisite. It doesn't explicitly contrast with add_to_list or list_lists, but the context is sufficient for selecting this tool.

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 full burden. It discloses ownership requirements but omits critical behavioral traits for a destructive operation, such as whether deletion is permanent, cascading, or what happens on failure. This is insufficient for a delete 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?

The description is a single, front-loaded sentence that conveys the essential purpose with no filler or redundancy. Every word 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 delete tool with no annotations and no output schema, the description is minimally viable but lacks important context such as permanence, error handling, and side effects. It does not fully prepare an agent for the consequences of invoking the 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 description coverage is 0%, and the parameter 'id' has no schema description. The description does not explicitly state that id is the list identifier, though it can be inferred from the tool name and context. The description adds minimal value 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 clearly states the action (delete) and the resource (a list you own), distinguishing it from siblings like create_list, get_list, and list_lists. The ownership condition adds specific scope.

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: use when you want to delete a list you own. However, there is no explicit comparison to alternatives like delete_saved_search or guidance on when not to use it. The ownership prerequisite is a minimal form of 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?

With no annotations, the description must disclose behavioral traits. It notes the ownership restriction but does not mention that deletion is permanent, any error behavior, or consequences. The lack of detail leaves significant ambiguity for a destructive operation.

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 concise sentence, front-loading the verb and clearly stating the resource. It contains no filler and is appropriately sized for a simple tool.

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 the tool's simplicity, the description is minimal but omits critical context such as how to locate the saved search ID, whether the action is irreversible, and behavior for non-existent or non-owned searches. This is insufficient for an agent to confidently invoke the 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?

The input schema provides only an 'id' string with no description. The description does not explain what 'id' refers to or how to obtain it, leaving the parameter semantically underspecified. The coverage is 0%, and the description fails to compensate.

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 identifies the resource ('saved search') and the action ('delete'), with an ownership qualifier ('you own'). This distinguishes it from sibling tools like delete_list and from non-deletion saved-search 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 implies use when a saved search owned by the caller needs to be removed, but it doesn't explicitly state when to use this over alternatives (e.g., delete_list) or mention prerequisites like obtaining the ID via list_saved_searches. Context is inferred rather than stated.

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 full burden of behavioral disclosure. It reveals that the tool resolves various identifier types, returns only the requested groups, and separates free vs. paid groups. It does not disclose potential errors or side effects, but for a read-style enrichment tool this is sufficient transparency.

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 moderately long but every sentence earns its place. It is front-loaded with the core promise ('One call, pick your field groups'), then contrasts with the alternative, and finishes with a compact list of groups and pricing. It is well-structured and not verbose.

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 only 2 parameters, no output schema, and no annotations, the description provides sufficient context: it explains the purpose, the input flexibility, the available groups, and the pricing distinction. It lacks details about return structure, but given the tool's simplicity and no output schema, this is 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?

The schema already covers both parameters, but the description adds meaningful semantics beyond the schema by listing valid field groups (profile, onboarding, artifacts, rating, security, insights) and their free/Pro status, plus the default set. This helps the agent understand what values to pass for 'fields' and what 'id' accepts.

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's function: 'one call, pick your field groups' and 'resolves a slug OR any identifier and returns exactly the groups you ask for'. It distinguishes from siblings by explicitly naming the chaining alternative (get_provider + get_provider_rating + get_provider_artifacts + get_provider_onboarding), making its unique value proposition clear.

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 positions the tool as a replacement for chaining multiple provider-related tools, saying 'instead of chaining...'. It also provides guidance on group availability with '(free)' and '(Pro)' labels, indicating when certain groups require a Pro plan. This gives clear context for when to use the tool versus alternatives.

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 behavioral burden. It discloses the license requirement, attribution expectations, and dataset contents, but doesn't address output format, access controls, or error conditions. These gaps leave some uncertainty for the agent.

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 compact, providing key information in two sentences. The structure is slightly convoluted with parentheticals, but it's efficient and not 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?

The description covers the core purpose and the two dataset variants, but omits practical details such as output format, file size, authentication/license verification steps, and failure modes. For a simple export tool with no output schema, more context would be helpful.

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 description explains the meaning of the `dataset` parameter by detailing the contents of ratings (facets, trend, rubric, provenance) and providers (coverage, score), which goes beyond the schema's enum. The `co_brand` parameter is already well-described in the schema, so the description effectively compensates for the schema's 50% coverage.

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 exports the whole dataset (ratings or providers) in one pull, distinguishing it from a 100-row page. It names the two dataset options and describes their contents, making the purpose specific and actionable.

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 specifies this is a BUSINESS/license tier feature intended for media outlets and analysts, and contrasts it with a page-limited view. It doesn't name alternative tools explicitly, but the context clarifies when the full dataset export is appropriate.

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 the output format ('APIs.json document with an Arazzo hint') and intended use ('the team can commit'), but does not state whether the operation is read-only, has side effects, or requires specific permissions. The verb 'Export' implies non-destructive behavior, but explicit disclosure is missing.

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 sentence that front-loads the verb and resource, with no redundant filler. The 'PRO —' prefix is a concise indicator of availability and does not detract.

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, output, and use case adequately for a two-parameter tool with no output schema. It lacks explicit information about the return value or side effects, but the output artifact and intent are clear, making it sufficiently complete for an agent.

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%, with 'capabilities' and 'region' documented. The description does not add parameter-specific information beyond what the schema already provides, so a baseline of 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 uses the specific verb 'Export' with a clear resource ('designed capability stack') and output ('adoptable APIs.json document'), which distinguishes it from sibling tools like export_dataset. It is specific and unambiguous.

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 when to use it (when you have a designed stack to export) but does not explicitly name alternatives or exclusions. The phrase 'designed capability stack' differentiates it from export_dataset, though no direct comparison is 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?

With no annotations, the description carries the burden of behavioral disclosure. It does reveal pagination, sorting, and filter capabilities, which are useful. However, it doesn't mention output shape, default sort/pagination behavior, or access/rate-limit implications, leaving moderate gaps.

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: the first front-loads the core action and scope, the second gives a prioritization pointer to a sibling tool. No wasted words, and the structure is easy to scan.

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 the tool's complexity (19 parameters, no output schema, no annotations), the description provides a strong high-level orientation and usage priority, but lacks return-format details, default ordering/pagination behavior, and any mention of how summary vs full views affect results. It's adequate but leaves meaningful gaps for an agent.

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 53%, so the description adds value by naming several filter dimensions (tag, provider, artifact type, industry, region, rating band) that map to schema parameters. Still, many parameters (q, page, limit, area, match, etc.) are left to schema names/descriptions, and the description doesn't fully compensate for the undocumented half.

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 specific verb 'list' with a clear resource ('APIs across providers') and enumerates filter dimensions (tag, provider, artifact type, industry, region, rating band). It also distinguishes from sibling tools like apis_io_search by positioning this as the paginated, sortable API-centric list.

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 directs users to 'Use apis_io_search first for a cross-type overview,' which gives clear context for when to prefer another tool. It doesn't enumerate all exclusions (e.g., when to use find_providers or get_api), but the guidance is helpful and unambiguous.

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 full burden. It discloses that include=["content"] inlines bodies, implying default behavior omits bodies. It also conveys the scope of search (APIs.json documents). It omits rate limits, pagination details, and match semantics, but for a read-only search tool this is adequate.

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 four short sentences or sentence fragments, every one adds value: scope, target items, filtering options, and an alternative. No fluff or repetition.

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 the main purpose, key filtering, and an alternative, but lacks information about the return format and match behavior. Since there is no output schema, some description of expected results would be valuable. However, it still provides a solid foundation 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 description coverage is only 29%, so the description must compensate. It explains q, tags, providers, and include (adding the 'inlines bodies' behavior), but leaves page, limit, and match unexplained. This is incomplete but better than nothing.

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 specifies that the tool searches APIs.json discovery documents across the catalog, making its purpose distinct from generic API search. The wording is fragmented, but the meaning is clear and distinguishes from sibling tools like find_apis and find_artifacts.

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 directs users to find_artifacts for cross-type search, providing an alternative. It also lists primary filters (q/tags/providers) and the include option, giving clear usage context. However, it doesn't compare against all possible sibling tools or elaborate on when not to use this tool.

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 discloses behavioral details such as filtering capabilities and the 'include=["content"]' option that inlines bodies. While it omits pagination and return format, these are less critical for a search tool, and the description adds valuable context beyond 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?

The description is concise, using four short sentences to convey the core purpose, definition, filters, and alternative. No filler or repetition; every sentence adds 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 search tool with 7 params and no output schema, the description provides enough to select and invoke correctly: it names the resource, key filters, include behavior, and a cross-type alternative. It misses some details like match semantics, but overall is sufficiently complete for accurate use.

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 only 29%, so the description compensates for some parameters: it explains q/tags/providers filtering and the include option's semantics. However, it does not address page, limit, or match, leaving these under-documented despite the low coverage.

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 identifies the tool's purpose: finding Arazzo workflows, defined as multi-step API workflows chaining operations. It distinguishes this tool from siblings by specifying the resource type (Arazzo workflows) and mentions cross-type alternatives, making its purpose unambiguous.

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 states when to use this tool for searching Arazzo workflows and points to an alternative: 'Use find_artifacts for cross-type search.' This provides clear context for selection among many find_* siblings.

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?

There are no annotations, so the description carries the full burden of behavioral disclosure. It adds useful context by describing the areas as 'curated, scored provider indexes' and mentions text search and sorting, but it does not disclose return format, pagination behavior, auth requirements, or other side effects. This is a read-only search tool, but the description could be more explicit about result structure and potential limitations.

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 concise, two sentences, and front-loaded with the primary purpose. Every word earns its place: subject, examples, and key capabilities without unnecessary fluff. It is appropriately sized for a simple search tool.

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?

There is no output schema, so the description takes on the job of explaining return values, which it does not do. It also does not mention whether results include IDs or that get_area could be used for details, which is a gap given the sibling tool context. The description covers the 'what' and 'how' but lacks result format and integration cues.

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 no parameter descriptions (0% coverage), but the description partially compensates by stating 'Search by text' (for q) and 'sort by provider count' (for sort). It does not add meaning for page or limit, though their names imply pagination. Given 4 parameters and incomplete coverage, this is adequate but not rich.

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 browses the 'API Evangelist areas taxonomy' with concrete examples (authentication, webhooks, payments), and it explicitly mentions search-by-text and sort-by-provider-count capabilities. This specific verb+resource combination distinguishes it from sibling tools like find_apis or find_providers, making the purpose unambiguous.

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 usage by indicating the tool searches the areas taxonomy, but it does not provide explicit when-to-use/when-not-to-use guidance or name any alternative tools. Given many sibling find_* tools exist (e.g., find_tags, find_industries), the lack of exclusions leaves room for confusion about when to choose this over similar ones.

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 transparency burden. It discloses that 'include=["content"] inlines bodies', but omits auth prerequisites, output shape, pagination behavior, and leaves the 'PRO: scopes, security' line ambiguous.

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 core purpose and uses compact, purposeful sentences. The long type list is justified because it enumerates valid values, though the 'PRO' phrase could be clearer.

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 a 7-parameter search tool with no annotations and no output schema, the description is incomplete. It lacks return value expectations and parameter semantics for most filters, and the ambiguous 'PRO' note introduces confusion.

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?

With 0% schema description coverage, the description must compensate, but it only clarifies the 'type' enum and the 'include' behavior. The semantics of 'q', 'tags', 'providers', 'page', and 'limit' remain unexplained.

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 ('Find'), a target resource ('artifacts'), and scope ('ANY one type across the catalog'), clearly framing it as the cross-type entry point. It also distinguishes this tool from the dedicated find_<type> tools, making its 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 gives explicit guidance: prefer dedicated find_<type> tools when you know the type, and use this tool when not. This directly addresses the alternatives and provides a clear decision rule.

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 burden. It reveals that include=['content'] inlines bodies and that the tool is scoped to AsyncAPI/event-driven specs, but it does not disclose pagination behavior, authentication needs, or other potential effects. Some behavioral context is provided, but significant gaps remain.

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 extremely concise: two sentences deliver purpose, scope, key filters, include behavior, and an alternative tool. Every sentence earns its place with no redundant content.

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 search tool with 8 parameters, no annotations, and no output schema, the description covers the core purpose, scope, filtering options, an important behavior (inlined bodies), and an alternative. It omits details like pagination and match semantics, but these are inferable or less critical. The description is largely sufficient.

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 only 38%, meaning most parameters lack schema descriptions. The description adds meaning to include (inlines bodies) and providers, but page, limit, and match are left undocumented in both the schema and description. It partially compensates for the low coverage but not fully.

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 identifies the tool as finding AsyncAPI (event-driven) specifications, distinguishing it from sibling tools like find_openapis and cross-type find_artifacts. While the verb 'find' is only in the tool name, the description's content makes the purpose unambiguous.

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 states how to use the tool ('Filter by q / tags / providers'), documents the include parameter's effect, and names find_artifacts as the alternative for cross-type search. This gives clear, actionable usage 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?

With no annotations provided, the description carries the transparency burden. It discloses that include=['content'] inlines bodies and specifies these are individual channels, which is useful behavioral context. It does not mention pagination or rate limits, but this is a read-only search tool, so the disclosure is adequate.

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, no wasted words. Purpose is front-loaded, followed by filter options and an alternative tool reference. Every sentence contributes to understanding.

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?

Covers the core purpose, key filtering options, and the cross-type alternative in a compact manner. No output schema exists, but the return type (list of channels) is implied. It omits match semantics and pagination details, but these are in the schema and the description is otherwise complete 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 only 38%, but description adds meaning for q, tags, providers, and include (inlining bodies). However, parameters like match, page, limit, and protocol are not explained in the description, leaving the agent to rely on incomplete schema details.

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 clearly states the tool finds AsyncAPI event channels (topics/streams), with a specific resource and scope. It also distinguishes from find_artifacts by pointing to cross-type search, making its unique purpose unambiguous.

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 provides an alternative: 'Use find_artifacts for cross-type search,' which tells the agent when not to use this tool. Also implies usage by narrowing to individual event channels and listing filter options, giving clear context.

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 reveals that collections are runnable and that include inlines bodies, but does not disclose return format, pagination, or any side effects. For a read-only find operation, this is adequate 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, front-loaded with the core purpose, no redundant phrases. 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 an 8-parameter tool with no output schema and no annotations, the description is reasonably complete. It explains the core functionality, filtering, the include effect, and points to an alternative. However, it does not describe the response structure, which the schema also omits.

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 low (38%), but the description adds meaning by explaining that include=['content'] inlines bodies and that q/tags/providers are filters. This goes beyond the bare schema, though page, limit, sort, and match are left to 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 clearly states the tool finds Postman/Open collections across the catalog, with 'Runnable request collections' adding specificity. The explicit reference to find_artifacts for cross-type search distinguishes this 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?

It provides specific usage context: 'Filter by q / tags / providers' and 'include=[content] inlines bodies', and gives an explicit alternative: 'Use find_artifacts for cross-type search.' This tells the agent when to use this tool versus another.

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 transparency burden. It discloses the Fortune 1000 scope and the ranking by technology-readiness signal, and indicates the tool is free. However, it does not mention authentication requirements, response format, pagination details, or any limitations on search behavior, leaving some important behavioral aspects unaddressed.

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 concise sentence that packs multiple key facts: browse companies, Fortune 1000 scope, name search, ranking by tech-readiness, and free discovery. Every phrase contributes value, and it is front-loaded with the primary action.

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 has no output schema and no annotations, so the description needs to convey essential usage context. It provides the high-level purpose and ranking but lacks details on result structure, pagination, or authentication. For a simple discovery tool, this is adequate but not comprehensive; an agent might still be uncertain about the exact output format and how to construct queries.

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%, so the description must compensate. It implicitly explains the 'q' parameter as a name-based search ('by name'), but provides no guidance on 'page' and 'limit' except what the schema defaults and constraints already imply. This leaves the majority of parameters semantically under-specified.

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's action (browse) and resource (profiled companies within Fortune 1000). It distinguishes itself from siblings like get_company_insight by focusing on ranked discovery by name, and mentions 'free discovery' as an additional differentiator.

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 provides clear context that this tool is for browsing/discovering companies by name with a technology-readiness ranking, implying it is suitable for exploratory search. However, it does not explicitly mention when not to use it or name alternatives, so it lacks explicit exclusions.

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 burden. It adds the useful detail that including 'content' inlines bodies, which goes beyond schema. However, it doesn't disclose pagination, sorting behavior, or the structure of returned examples, leaving gaps.

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?

Four short sentences, each with purpose. The key information (what, filters, include behavior, alternative) is front-loaded, with 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?

For a read-oriented search tool, the description covers core usage and a key alternative, but omits pagination and matching behavior. With no output schema, the description gives only a vague sense of the return value, so it's not fully 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 coverage is only 38%, so the description must compensate. It explains q, tags, providers as filters and include as controlling body inlining. It does not mention page, limit, match, or sort semantics, so coverage remains incomplete.

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 'Example payloads across the catalog' and 'Real request/response examples', clearly indicating the tool retrieves example payloads. It distinguishes itself from find_artifacts by explicitly directing cross-type searches there. However, it lacks an actionable verb in the text itself, relying on the tool name.

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 explicit filtering guidance ('Filter by q / tags / providers') and an alternative ('Use find_artifacts for cross-type search'). This tells the agent when not to use this tool. It doesn't enumerate all possible use cases, but the guidance 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?

No annotations provided, so description carries full burden. It discloses the 'include=content' inlines bodies behavior, which is useful. However, it doesn't describe the return format, pagination defaults, or explicitly state that this is a read-only search, leaving some behavioral expectations implicit.

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 concise sentences. The first defines the domain, the second gives filters and an alternative tool. Every word is purposeful, no fluff.

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 8 parameters, no output schema, and no annotations, the description covers core usage but misses details like pagination, match behavior, and response structure. It's adequate for a simple search tool but not as rich as possible.

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 only 38%, but the description compensates by explaining key parameters: q, tags, providers, and include. It adds meaning for 'providers' (which has no schema description) and clarifies that include inlines bodies. However, it doesn't explain match semantics or billing_model beyond its schema description.

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 identifies the tool's purpose: searching FinOps/billing models, explaining they define how usage is metered and billed. It distinguishes itself from the sibling find_artifacts by explicitly noting cross-type search should use that 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?

Provides concrete usage guidance: filters by q, tags, providers, and the include parameter for inlining content. Explicitly states when to use an alternative (find_artifacts for cross-type search), which differentiates it from many sibling tools.

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 filtering behavior and that include=[content] inlines bodies, but does not explain pagination (page/limit), match semantics, output format, or what 'bodies' entails. Adequate for a read-only search tool 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?

Four short chunks, each earning its place: purpose, clarification of type systems, filter options, and cross-reference to sibling tool. No wasted words.

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 search tool with no output schema and no annotations, the description covers purpose, main filters, and a sibling alternative, but omits behavioral details like pagination and match logic. It's usable but incomplete for a no-annotation context.

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 only 29% (q and tags). The description adds semantics for providers and include (inlining bodies), but leaves page, limit, and match unexplained. It partially compensates for poor schema coverage but not fully.

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 states the tool finds GraphQL schemas/type systems in the catalog, and distinguishes it from find_artifacts for cross-type search. However, it lacks an explicit verb (relying on the name) and is written as noun fragments rather than a full sentence, so it's clear but not maximally explicit.

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 names find_artifacts as an alternative for cross-type search, implying this tool is for GraphQL-specific queries. Also lists the main filterable fields (q, tags, providers), giving concrete usage context.

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 must fully disclose behavior, but it only mentions sorting by provider/API count. It omits pagination behavior, search capabilities, and output structure. This is insufficient for the agent to predict tool 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?

The description is extremely brief and contains no redundant information, but it is under-specified given the tool's parameter set. The single sentence omits necessary details, so conciseness is not a strength here.

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 the absence of annotations, output schema, and parameter descriptions, this terse description leaves major gaps. The agent cannot determine acceptable sort values, pagination defaults, or what results look like. The description is inadequate for effective tool 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?

Schema coverage is 0%, so the description should explain each parameter, but it only vaguely references sorting. The q, page, and limit parameters are entirely undocumented. The description adds minimal value for parameter understanding.

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's function: browsing industry verticals with sorting capability. It implies a list/browse operation distinguishing it from get_industry or industry_gap_analysis, though it does not explicitly name alternatives. It is still a specific verb+resource description.

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?

No guidance is provided on when to use this tool versus alternatives like get_industry or industry_gap_analysis. The description only states what it does, not when it should be chosen. This leaves the agent to infer usage context.

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 the core output (backing VC firms) and that the tool is free, but does not mention response format, error handling, rate limits, or authentication. For a read-only find tool this is acceptable but not particularly transparent.

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 line with a clear explanation and a cost note. No wasted words, front-loaded with the core mechanism, and appropriately sized for the tool's simplicity.

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 the tool's simplicity (one param, no output schema, no annotations), the description covers the essential input and output concept. It lacks explicit return format or examples, but for a basic directed lookup it is complete enough.

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 one required string parameter 'slug' with zero description. The description adds that the slug identifies a provider/company, but does not define slug format, how to obtain it, or constraints. This is minimal compensation for 0% schema coverage.

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 identifies which VC firms back a given provider/company by slug. The phrase 'reverse portfolio' distinguishes it from vc_portfolio, making the purpose precise and differentiated 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 implies the use case (given a company, find its investors) and the 'reverse portfolio edge' hints at contrast with portfolio lookups. However, it does not explicitly name an alternative tool or provide explicit when-to-use/when-not-to-use guidance, so it falls 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?

No annotations are provided, so the description carries the full burden. It discloses a key behavioral detail: 'include=["content"] inlines bodies,' which informs the agent about payload behavior beyond the schema. However, it does not state read-only status, pagination limits, or any other side effects. For a search tool this is acceptable but not comprehensive.

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 but contains a redundant fragment: 'Linked-data vocabularies.' adds little beyond the first sentence. The remaining sentences are efficient, but overall structure could be tighter.

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 has 8 parameters, no output schema, and no annotations. The description covers purpose, key filters, and an alternative but omits return format, pagination, sorting, and match behavior. It is adequate for basic usage but not fully complete given the complexity.

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 low (38%), so the description must compensate. It does add meaning for undocumented parameters: providers is listed as a filter, and include's 'content' option is explained ('inlines bodies'). However, it does not mention page, limit, sort, or match semantics. It covers some gaps but not all, giving partial compensation.

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 resource: 'JSON-LD contexts across the catalog.' This is a specific verb-noun combination that distinguishes it from siblings like find_json_schemas or find_artifacts, and it even points to find_artifacts for cross-type search. The purpose is unambiguous and distinct.

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 names an alternative: 'Use find_artifacts for cross-type search.' This tells the agent when not to use this tool and when to prefer another. It also implies usage for JSON-LD contexts specifically, providing clear context for choosing this tool among many find_* siblings.

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 adds behavioral context beyond the name: it specifies that this is for standalones (not embedded), and that include=['content'] inlines bodies. It doesn't discuss response shape or rate limits, but for a read-only find operation the conveyed scoping and inline behavior are 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?

Two sentences, front-loaded with the core purpose, then precise filter and alternative instructions. No filler, every word 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?

Given the tool has 7 parameters, no output schema, and no annotations, the description covers the essential usage but omits details about pagination, match mode, and the return format. It is adequate for basic usage but could be more complete for an agent operating without additional context.

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 only 29% (2 of 7 parameters described). The description compensates by explaining the roles of q, tags, providers, and include, but leaves page, limit, and match unexplained. It adds meaning beyond the schema for the main filters, but does not fully cover all 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 clearly identifies the tool's purpose: finding standalone JSON Schemas in the catalog. It distinguishes from siblings by explicitly mentioning 'Standalone data schemas' and pointing to find_artifacts for cross-type search, making the resource scope unambiguous.

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 states how to filter (by q / tags / providers) and when to use an alternative ('Use find_artifacts for cross-type search'). This gives clear when-to-use and when-not-to-use guidance, fully satisfying this dimension.

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 must carry the full burden. It discloses the effect of include=['content'] (inlines bodies), but does not mention auth requirements, read-only nature, pagination, or other side effects. This is a moderate gap.

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 concise sentences with front-loaded purpose, followed by essential filtering and alternative guidance. No wasted words.

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 9 parameters, no output schema, and no annotations, the description provides a basic overview but omits return format, pagination behavior, and default/constraint details. It is adequate but incomplete for fully guiding an agent.

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 44%, so the description should compensate. It explains the 'include' parameter's effect and reiterates q/tags/providers filtering, but does not add meaning for page, limit, match, or struct_type, which remain underdocumented.

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 identifies the resource ('JSON Structures') and implies discovery/search, but lacks a strong imperative verb. It distinguishes from sibling find_* tools by clarifying the focus on data structures and explicitly referencing find_artifacts for cross-type search.

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 mentions when to use find_artifacts instead ('Use find_artifacts for cross-type search') and describes primary filtering capabilities, giving clear usage context relative to alternatives.

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 discloses that include=['content'] inlines bodies and that filtering is available, but it omits behavioral details like pagination, return format, and read-only safety. These omissions leave the agent with incomplete expectations.

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 three concise sentences, front-loaded with the core purpose, then filters, and then an alternative. Every sentence adds value and there is no redundant or filler content.

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 the tool has 8 parameters, no output schema, and no annotations, the description covers the main filtering options and one sibling alternative but omits key context such as pagination defaults, match semantics, and the shape of returned data. This leaves moderate gaps for an agent.

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 only 38%, so the description must compensate. It adds meaning for q, tags, providers, and include, but leaves page, limit, match, and install_method unexplained beyond the schema. This partial compensation is insufficient for full clarity.

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 identifies the tool's purpose: searching MCP servers in the catalog. It provides a definition ('Model Context Protocol servers a provider offers to agents') and specifies filter capabilities, distinguishing it from the sibling tool find_artifacts for cross-type search.

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 explicit guidance on filtering by q, tags, and providers, and instructs to use find_artifacts for cross-type search, offering a clear alternative. However, it does not elaborate on when to prefer find_mcp over other find_* siblings, leaving some room for 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 must carry behavioral disclosure. It adds useful context about filtering and inlining bodies, but it does not state the read-only nature, pagination behavior, or return format. While not contradictory, it leaves significant behavioral details uncovered.

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 compact, with no filler words. It front-loads the resource and then provides key usage and alternatives in a few short 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?

For a search tool with 7 parameters, no annotations, and no output schema, the description covers purpose, main filter options, and alternatives, but it omits the return format and pagination details. It is adequate but not fully 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 coverage is low (29%), but the description adds meaning by naming q/tags/providers as filters and clarifying that include=['content'] inlines bodies. However, it does not explain the match, page, or limit parameters, leaving gaps for those without schema 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 identifies the resource ('OpenAPI specifications across the catalog') and the action (filtering via q/tags/providers or inlining content). It distinguishes itself from get_openapi (single spec) and find_artifacts (cross-type search). The verb is implied by the tool name and the filter instructions.

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 an alternative: 'get_openapi returns one API's primary spec' implies using that for single-spec retrieval, and 'Use find_artifacts for cross-type search' names an explicit alternative. This provides clear when-to/not-to 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?

With no annotations, the description must carry the behavioral disclosure burden. It does add one useful trait: 'include=["content"] inlines bodies,' which explains a parameter's effect. The description also implies a read-only search operation via 'Filter by...' but does not explicitly state return behavior, pagination, or any side effects. For a simple read-only list tool, this is adequate 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?

The description is two sentences, tightly written, and front-loaded with the core purpose. Every clause contributes: scope, clarification as tier, filter options, include behavior, and an alternative. There is no extraneous content or repetition of schema details.

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 has 8 parameters, no output schema, and no annotations, so the description carries significant weight. It covers the what, the main filters, one behavior, and an alternative, but it does not explicitly state the return shape or mention pagination/sorting defaults. Given its simplicity, it is adequate but not fully self-contained.

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 only 38%, so the description should compensate. It clarifies that q, tags, and providers act as filters, and it explains the effect of include (inlines bodies). However, it does not add meaning for sort, page, limit, or match, leaving those parameters underexplained. The description adds partial value but does not fully compensate for the low schema coverage.

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 identifies the tool's subject as 'Pricing plans across the catalog' and further clarifies these are 'An API's pricing tiers.' The name 'find_plans' combined with this description conveys a search/list function, and it distinguishes itself from sibling tools like find_artifacts by narrowing to pricing plans. However, it lacks an explicit verb (e.g., 'Find' or 'List'), so it falls slightly short of a fully explicit purpose statement.

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 clear context: this tool is for pricing plans, not cross-type search. It explicitly names an alternative: 'Use find_artifacts for cross-type search.' It also mentions the filter capabilities (q, tags, providers) which helps the agent choose. However, it does not provide exhaustive 'when not to use' guidance relative to other close siblings like find_apis or get_provider, so it is not a full 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?

Discloses the key behavioral trait that collections are returned by reference unless include=['content'] inlines bodies. Since there are no annotations, this adds valuable context. It stops short of mentioning pagination behavior, but for a read-only find tool this is a solid level of transparency.

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, information-dense sentences. The core purpose is front-loaded, and every sentence adds value without redundancy or 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?

For a 7-parameter tool with no output schema and no annotations, the description covers the core search behavior, filters, the by-reference/inline distinction, and the alternative tool. It omits explicit details on match and pagination, but these are partially inferable from the schema. Overall, sufficiently complete for typical usage.

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 description adds meaning for include (inlines bodies) and providers (filter by providers), and references q/tags. However, schema description coverage is only 29%, and the match parameter (any vs all) is left unexplained, leaving ambiguity for filter combination 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 clearly states that this tool returns Postman-format collections across the catalog, with the specific resource and scope. It also distinguishes itself from find_artifacts by noting that cross-type search should use that alternative.

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 mentions filters (q/tags/providers) and points to find_artifacts for cross-type search, providing clear when-to-use and when-not-to-use guidance with an alternative 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?

No annotations are provided, so the description must carry the burden. It discloses pagination and sortability, but omits side effects, authentication, rate limits, or the shape of the response. Given zero annotation coverage, this is a significant gap.

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 primary purpose and filter capabilities, followed by a clear usage directive. No wasted words; 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?

With 19 optional parameters, no output schema, and no annotations, the description is too brief. It omits default behaviors (e.g., sort default when no query), summary vs full view implications, and any guidance on response structure. A longer description or output schema is needed for this complexity.

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 about 53%, so the description partially compensates by naming filter dimensions like artifact type, industry, and region that lack schema descriptions. However, it does not explain array value formats or the match 'any/all' behavior, and some parameters remain undocumented.

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?

Clearly states it is a paginated, sortable list of providers with multiple filter dimensions (text, tag, artifact type, industry, region, rating band, access model). The verb 'find' plus resource 'providers' distinguishes it from sibling tools like find_apis and find_areas.

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 instructs to 'Use apis_io_search first for a cross-type overview', providing a direct alternative and a precedence guideline. This helps the agent decide when to use this tool versus a broader search tool.

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 of behavioral disclosure. It mentions that 'include=["content"] inlines bodies' and the scope 'across the catalog,' but does not state the read-only nature, pagination behavior, or response format. This is a moderate gap for a find 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?

The description is compact and front-loaded, identifying the resource first and then packing filtering, include behavior, and an alternative into two sentences. There is slight redundancy between 'rate-limit policies' and 'declared throttling policies,' but no waste.

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?

No output schema exists, so the description should hint at return values, but it remains silent. It covers the key filtering and alternative usage, but fails to mention pagination or what fields are returned. Given the 8-parameter complexity, the description is adequate but incomplete.

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 low (38%), but the description adds meaning for q, tags, providers, and include (filtering vs inlining). It does not explain page, limit, sort, or match, though sort has a schema description and the others are standard pagination/boolean options. The description partially compensates for the low coverage.

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 identifies the tool as finding 'rate-limit policies' and clarifies with 'Declared throttling policies.' It distinguishes from siblings by directing cross-type searches to 'find_artifacts,' making the resource and scope unambiguous.

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 filtering guidance ('Filter by q / tags / providers') and an alternative tool ('Use find_artifacts for cross-type search'). However, it does not explicitly state when not to use this tool beyond that cross-type search case, so it's clear but not exhaustive.

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 must carry the transparency burden. It adds useful context such as the 'PRO' access prerequisite and the temporal window ('since the previous scoring build'), but it does not disclose return format, ordering behavior, or any rate limits or side effects. The disclosure is partial but not misleading.

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, compact sentence that front-loads the 'PRO' access tag and immediately conveys the core function. There is 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?

Given the simplicity of the tool (one optional parameter, no output schema), the description covers the essential purpose and temporal scope. However, it does not explicitly state what entities are returned (e.g., providers) or what fields are included, so a bit more detail would improve completeness.

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's 'limit' parameter is documented only by name, type, default, and min/max constraints, with 0% description coverage. The tool description does not mention 'limit' at all, so the agent must infer its meaning from the parameter name alone. The description fails to compensate for the missing schema-level description.

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 specifies the tool's action ('find'), the resource ('rating movers'), and the precise scope ('biggest ... up and down since the previous scoring build'). This clearly distinguishes it from sibling tools like get_rating_history or whats_changed, which cover different rating-related queries.

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 provides clear context for when the tool is relevant—when the user wants the largest rating changes since the last build. However, it does not explicitly state when to avoid this tool or mention alternative tools like get_rating_history or find_ratings, so usage guidance is implied rather than explicit.

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 of behavioral disclosure. It explains the default sort, the meaning of delta as 'biggest gainers', and filter dimensions. However, it does not disclose pagination behavior, the meaning of 'trend', or what response shape to expect, leaving gaps for a tool with 9 parameters.

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 concise at two sentences, front-loaded with the core purpose ('Ranked ratings leaderboard'), and every clause adds value: filters in the first sentence, sort options in the second. No redundancy or fluff.

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 9 parameters, no output schema, and no annotations, the description provides a solid high-level understanding but omits details on pagination, tags filtering, and exact behavior of 'trend' and 'facet'. It is adequate for basic usage but not fully complete for advanced scenarios.

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 only 11%, so the description must compensate. It adds meaning for band, score range, trend, facet threshold, and sort types, but leaves page, limit, tags, and the facet parameter itself unexplained. The description partially bridges the gap but does not fully cover all 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 clearly defines the tool as a 'ranked ratings leaderboard' with specific filtering and sorting capabilities. It distinguishes itself from siblings by emphasizing leaderboard ranking by composite, delta, or individual quality facets, which is not covered by single-rating or history 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 provides clear context for when to use the tool: to obtain a ranked, filterable leaderboard of provider ratings. It does not explicitly name alternatives or exclusions, but the filtering and sorting options make the intended use obvious in the context of sibling tools like get_provider_rating or find_rating_movers.

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 must carry the full burden. It only mentions sort-by-provider/API-count; it doesn't disclose pagination behavior, response format, or any side effects. 'Browse' implies read-only but that is inferred, not stated.

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 sentence with two clear clauses. It is front-loaded, concise, and every word adds value. No redundancy or fluff.

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 4 parameters, no schema descriptions, no annotations, and no output schema, the description is far too sparse. It lacks parameter semantics, sort options, return format, and region-specific context. This is a minimal list tool that should provide more guidance.

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%, so the description must compensate. It only hints at sort semantics ('provider/API count') and leaves q, page, limit, and valid sort values unexplained. This is insufficient for a 4-parameter tool.

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+resource: 'Browse geographic regions' and adds a specific capability: 'sort by provider/API count.' This distinguishes it from sibling find tools that target other entities like areas, industries, or providers.

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 usage is implied ('Browse geographic regions') but there are no explicit alternatives or when-not-to-use instructions. Given the large sibling set, the description gives clear context but no exclusions, so it falls short of a 4.

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 discloses the scope ('across the catalog'), the special behavior of include=['content'] to inline bodies, and the domain of the rulesets. It does not mention auth, rate limits, or return format, but for a read-only search tool these are less critical.

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 earning its place: what the tool returns, how to filter/include, and an alternative. No filler 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?

Given 8 parameters, no annotations, and no output schema, the description covers the core search behavior, filtering, and inline content. It misses some parameter details, but those are partially covered by the schema and are secondary 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 description coverage is only 38%, and the description adds meaning for 'providers' and the 'include' behavior (inlines bodies). However, it does not explain 'match', 'page', 'limit', or 'sort' beyond what the schema provides, leaving some parameter semantics under-specified.

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 specifies a clear verb+resource: 'Spectral governance rulesets across the catalog' and 'API design/linting rulesets'. It clearly distinguishes this from sibling tools like find_artifacts by stating 'Use find_artifacts for cross-type search.'

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 usage context: filtering by q/tags/providers, include=['content'] for inlined bodies, and points to find_artifacts as the alternative for cross-type search. This gives both when-to-use and when-to-use-another-tool 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?

No annotations are provided, so the description must disclose behavior. It mentions the 'Pro tier' access requirement and that include=['content'] inlines bodies, but it does not describe the return format, pagination behavior, or any side effects (e.g., read-only vs. mutation). The lack of output schema makes this a significant gap.

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 but includes redundant fragments like 'OAuth scope catalogs across the catalog' and 'Pro tier.' as a standalone fragment. It could be tightened to convey the same information in fewer words without losing meaning.

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 8 parameters, no output schema, and no annotations, the description is incomplete. It only hints at filtering and one include option, leaving the return value, pagination, and access details unexplained. Sibling tools like find_artifacts are referenced only for cross-type search, but no other distinctions are made.

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 only 38%, so the description should compensate. It adds meaning for 'providers' (a filter) and 'include' (inlines bodies), but does not explain 'match' (any/all), 'sort' (scope_count largest first), or pagination parameters. Partial compensation, leaving several parameters ambiguous.

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 identifies the resource as OAuth scopes and the action as finding/cataloging them, distinguishing it from other find_* tools like find_artifacts. The phrasing 'OAuth scope catalogs across the catalog' is somewhat awkward but the second sentence clarifies the purpose.

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 a clear alternative for cross-type search ('Use find_artifacts for cross-type search') and implies this tool is for OAuth-scope-specific queries. It does not explicitly state when not to use this tool beyond the cross-type case, but the guidance is sufficient for basic 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?

No annotations are present, so the description carries the transparency burden. It discloses that include=['content'] inlines bodies and mentions Pro tier access, but does not clarify return format, sorting defaults, pagination, or the exact definition of security artifacts. Some behavioral detail exists, but significant gaps remain.

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 compact and information-dense, using short phrases to convey scope, categories, access tier, filters, and an alternative tool. Though slightly disjointed, each fragment serves a purpose and the overall length is appropriate.

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 8 parameters and no output schema or annotations, the description is not fully self-contained. It covers key filters and the main alternative, but omits pagination, sorting details, matching logic, and return structure. This is adequate for a competent agent but not comprehensive.

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 only 38% (q, sort, tags have descriptions). The description adds meaning for include (inlines bodies) and identifies q/tags/providers as filters, but it does not explain page, limit, or match semantics. It partially compensates for the schema gaps but leaves several parameters underdocumented.

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 identifies 'Security artifacts across the catalog' as the tool's focus, enumerating specific categories (Authentication, domain security, VDP, trust center). It explicitly contrasts with find_artifacts for cross-type search, so the scope is unambiguous.

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 provides an explicit alternative: 'Use find_artifacts for cross-type search.' It also notes the 'Pro tier' access requirement and lists filtering mechanisms (q/tags/providers), giving clear guidance on when to use this tool.

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 burden of explaining behavior. It discloses the matching mechanism (shared tags) but does not mention whether the operation is read-only, what the output format looks like, or any edge cases. For a read-oriented search tool, this is adequate 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?

The description is a single, front-loaded sentence that conveys the core functionality without unnecessary words. Every word contributes meaning.

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 low-complexity tool with two parameters and no output schema, the description provides the essential idea but lacks detail on return values and parameter usage. It is minimally sufficient but could be more complete for an agent to invoke it correctly without additional inference.

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%, so the description must compensate. It only mentions 'shared tags' and does not explain the 'aid' parameter or the 'limit' parameter (including its default and maximum). The schema provides type/constraints but adds no semantic meaning beyond that.

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's function: finding APIs similar to a given API based on shared tags. The phrase 'more like this' and 'by shared tags' distinguishes it from siblings like find_similar_providers and general search tools like find_apis.

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 when to use this tool (when you need tag-based API similarity) but does not explicitly state exclusions or compare to alternatives. It gives context ('more like this' and 'by shared tags') but no direct guidance on 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?

Since no annotations are provided, the description carries the full burden. It discloses the matching dimensions (tags, industry, region, artifact coverage) which is valuable behavioral context, but says nothing about read-only nature, result ordering, pagination, or other expectations.

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, focused sentence that immediately states the tool's purpose and key distinguishing criteria. No dead weight.

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 tool with no output schema, the description conveys the core function but omits details about limit behavior, response shape, or result sorting. It is adequate but not fully self-sufficient.

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 zero description coverage, and the description only vaguely refers to the input as 'a given one,' which maps to the slug but not with any format guidance. The limit parameter is completely unaddressed, so the description adds minimal semantic value over 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 clearly states the tool returns provider alternatives based on shared tags, industry, region, and artifact coverage. This distinguishes it from broader search tools like find_providers and from find_similar_apis by specifying the resource (providers) and scope (similarity criteria).

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 usage for a known provider, but does not explicitly state when to prefer this over other provider search tools. No alternatives or exclusions are mentioned, leaving the agent to infer context from the tool name and sibling set.

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 must carry the burden. It discloses the behavior of 'include=["content"'] inlining bodies and the scope ('across the catalog'), but does not mention whether results are read-only, paginated, or what the response structure looks like, which is notable for a 7-parameter search 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?

The description is concise and front-loaded, with the core purpose in the first sentence. The second sentence is slightly redundant ('Packaged agent skills'), but the rest is efficient. It earns its place overall.

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 and 7 parameters, the description covers the main search behavior and the key include option, but lacks details on pagination, match (any/all) semantics, and return format. It is adequate but leaves clear gaps for a tool of this complexity.

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 only 29% (2 of 7 params described). The description adds meaning for 'include' (inlines bodies) and clarifies that q/tags/providers are filters. However, it does not explain page, limit, or match semantics, leaving some parameters under-specified.

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 identifies the resource ('Agent Skills') and the verb ('find'), with scope ('across the catalog'). It distinguishes itself from the sibling find_artifacts by explicitly naming it as an alternative for cross-type search, making the purpose unambiguous.

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 guidance: 'Use find_artifacts for cross-type search' tells when to use an alternative. It also frames filtering by q/tags/providers and the include option, implying these are the primary use cases and giving context for 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?

Since no annotations are provided, the description carries the transparency burden. It discloses pagination and sortability, which are important behaviors, but does not mention read-only nature, default response formats, or any limitations. This is adequate but leaves gaps.

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, front-loaded with the core purpose and ending with a practical usage pointer. Every word adds value with no unnecessary detail.

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 straightforward list tool with no required parameters and no output schema, the description covers the main use case and a key alternative. It could mention get_tag for single-tag lookup, but this is not essential given the sibling context and the simplicity of the 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 description coverage is 67% (4 of 6 params described), so the baseline is 3. The description adds no parameter-specific meaning beyond the schema—it only hints at sorting/pagination already captured by parameter definitions. The undocumented page and limit are self-explanatory, so no additional compensation is needed.

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's function: a paginated, sortable list of tags in the taxonomy. This specific verb and resource distinguish it from sibling find_* tools, and the mention of apis_io_search further clarifies its scope.

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 an explicit alternative by recommending apis_io_search for cross-type overviews, implying find_tags is for tag-specific browsing. While not exhaustive, this gives clear context on when to use the tool vs. a key alternative.

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 full burden for behavioral disclosure. It adds useful details: results include a 'network-matched, rated portfolio graph,' and the default sort order is portfolio_on_network. However, it does not describe response structure, pagination behavior, or the meaning of 'network-matched,' leaving some behavioral aspects opaque.

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 extremely concise, with four short sentences that each provide distinct, non-redundant information: the search action, the result graph, sorting options, and cost. It is front-loaded with the primary purpose and wastes no words.

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 the tool's moderate complexity (6 optional parameters, no output schema, no annotations), the description covers the core behavior, result content, sorting, and even notes it is free. It lacks explanation of pagination and the exact meaning of portfolio metrics, but for a read-oriented search tool this is 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?

The schema documents q, tags, and category, but leaves sort, page, and limit undescribed. The description compensates for sort by listing all sortable fields and the default. However, it omits any explanation of page and limit, and schema coverage is only 50%, so the description does not fully bridge the gap.

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: 'Find venture-capital firms.' It clearly defines search dimensions (name, thesis tags, category) and distinguishes itself from likely siblings like find_investors by targeting VC firms rather than individual investors. The sorting options further clarify the tool's purpose.

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 usage through the stated search criteria and sorting options, but it does not explicitly say when to prefer this tool over alternatives like find_investors or get_vc. No exclusions or alternate tool references are provided, so usage guidance is primarily inferred from the purpose.

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 burden of behavioral disclosure. It explains that the tool returns catalog vocabularies, supports filtering by several parameters, and that including 'content' inlines bodies. While it doesn't mention pagination or what happens with no filters, this is reasonably transparent for a read-only find operation.

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 four short sentences, each contributing essential information. It is front-loaded with the purpose, then usage, then differentiation. No filler 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 tool with 7 parameters and no output schema or annotations, the description covers the core purpose, key filters, and a behavioral note about inlining bodies. It lacks details on pagination (page/limit) and match semantics, but these are common and inferable. The alternative to find_artifacts adds completeness.

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 low (29%), but the description compensates by explaining that q, tags, and providers are filters, and include with 'content' inlines bodies. It does not cover page, limit, or match, but the most important semantics are provided, adding value 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 clearly states the tool finds 'API vocabularies across the catalog' and specifies they are 'controlled vocabularies a provider publishes.' It distinguishes from siblings by explicitly recommending 'find_artifacts' for cross-type search, fulfilling the purpose clarity criterion.

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 gives concrete usage instructions: 'Filter by q / tags / providers; include=["content"] inlines bodies.' It also provides an explicit alternative: 'Use find_artifacts for cross-type search.' This clearly guides when to use this tool versus another.

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 full burden. It mentions 'PRO' indicating an access requirement but does not explicitly state whether the operation is read-only or any side effects. It does describe the output content in detail, which adds transparency about behavioral results.

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, information-dense sentence that gets straight to the point, listing the core outputs without fluff.

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 has no output schema and only two simple parameters. The description covers the main output dimensions (per-provider gaps, peer comparisons, scores, stack-level gaps), which is sufficient for a read-only analysis tool, though it doesn't specify the return format.

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 already includes descriptions for both providers and min_share (100% coverage). The description does not add additional parameter semantics beyond what the schema provides, hence baseline 3.

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 performs gap analysis for each provider, listing specific artifact types (MCP, Arazzo, Rules, Skills) and includes peer comparisons and stack-level gaps. This distinguishes it from sibling tools like company_gaps and industry_gap_analysis by focusing on per-provider artifact gaps and cross-provider stack analysis.

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 context on when this tool is appropriate: to identify high-value missing artifacts for a provider or stack compared to peers. However, it does not explicitly mention when to use an alternative tool or provide exclusions.

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 must disclose behavior itself. It does reveal that setting include=["content"] inlines artifact bodies, implying the default excludes them. However, it does not mention error handling, response structure, or authorization needs, leaving significant behavioral aspects undisclosed.

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 sentence that efficiently packs the core purpose, identifier format, and a key parameter behavior. There is no unnecessary wording or repetition.

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 the main purpose and an important parameter, but it leaves out artifact_types, does not describe the return format, and does not differentiate from closely related tools like get_api_artifacts or get_openapi. Given the absence of annotations and output schema, this incomplete context limits usability.

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 0% description coverage, so the description must compensate. It explains aid as 'provider:api-slug' and clarifies the effect of include. However, artifact_types is omitted entirely, leaving the meaning of this parameter unclear.

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's function: 'Full detail for one API' with a specific identifier format 'aid (provider:api-slug)'. It distinguishes from siblings like get_api_artifacts by emphasizing 'full detail' and 'inline artifact bodies'.

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 this tool is for retrieving detailed information about a single API, but it does not explicitly name alternatives or provide when-to-use vs when-not-to-use guidance. The phrase 'Full detail' offers context but lacks direct comparison to sibling tools.

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 transparency burden and does well: it reveals grouping by type, the by_type_counts summary, synonym-aware type matching, and inline content behavior. It does not mention pagination, auth, or error handling, but the key behavioral traits are 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?

The entire description is a single, information-dense sentence. Every clause adds valuable detail: grouping, type scoping, synonym behavior, and content inclusion. No filler 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?

Despite lacking an output schema and annotations, the description covers the main return summary (by_type_counts), filtering, and content inlining. It does not explain the full response format or pagination, but for a focused artifact retrieval tool, the provided context is sufficient for an agent to invoke 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?

Schema coverage is low (only type has a description), but the description compensates by explaining type scoping with synonym awareness and include content as inlining bodies. The 'aid' parameter is not explicitly detailed, but 'One API's' implies it is the API identifier.

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 indicates the resource (one API's artifacts) and the grouping behavior, distinguishing it from siblings like get_provider_artifacts and find_artifacts. However, it lacks an explicit verb such as 'List' or 'Get', relying on the tool name for the 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?

The description implies when to use the tool (for a single API's artifacts) and gives usage options (type scoping, include content), but it does not explicitly state when to prefer this over sibling tools or provide exclusions or alternatives. The context is clear but not fully explicit.

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 transparency burden. It discloses the 'top sample' behavior (not the full list), the presence of a total count, and a dedicated site link. It also mentions the view=full option, adding behavioral context beyond 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?

The description is two concise sentences with no extraneous information. The core functionality and usage alternatives are stated efficiently, making it easy to scan.

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 or annotations, the description outlines the response composition (metadata, site link, top sample providers with total) and provides both a deeper option (view=full) and a fallback (find_providers). It is adequate for a simple read tool, though it omits error handling or authentication details, which are acceptable gaps 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?

Schema covers 67% of parameters (view and limit have descriptions). The slug parameter is not described in the schema, but the description's reference to 'area=slug' clarifies its meaning. The view parameter behavior is well explained in the schema, and the description reinforces its role with the 'view=full' pointer.

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 that the tool returns a single area with 'metadata, its dedicated site link, and a top sample of member providers (with the total)'. It explicitly differentiates from find_providers for the full list, making its scope and resource unambiguous.

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 explicit usage guidance: 'Use find_providers?area=slug for the full list, or view=full here.' This tells the agent when to use get_area versus alternatives and how to obtain the full list.

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 must disclose behavioral traits, but it only states that it returns 'top-rated providers'. It does not explicitly state that this is a read-only operation, how results are sorted, or any pagination behavior. The 'PRO —' prefix adds no meaningful 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?

The description is short but wasteful, opening with an unexplained 'PRO —' prefix that adds no value. The remaining phrase is cryptic and arguably less informative than the tool name itself, making the structure ineffective despite its brevity.

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 has no output schema, no annotations, and a minimal description. It fails to explain what an 'area' is, what 'top-rated' means, what the response format includes, or any usage notes. This is insufficient for an agent to invoke the tool 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?

Schema description coverage is 0%, and the description does not explain the 'slug' or 'limit' parameters. The agent is left to infer that 'slug' refers to an area identifier and 'limit' is self-evident from the schema, but no additional meaning is added beyond 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 identifies the tool as returning 'top-rated providers' for a curated 'area', which is a specific resource with scope. The term 'area' distinguishes it from sibling tools like get_industry_leaders and get_region_leaders, though the meaning of 'API Evangelist' is ambiguous and not fully clarified.

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 provides no explicit guidance on when to use this tool versus alternatives such as get_industry_leaders or get_region_leaders. No context, prerequisites, or exclusions are given, leaving the agent without direction for tool 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 of behavioral disclosure. It does disclose the main data dimensions returned, which is useful, but it omits information about return format, authentication, rate limits, or what 'Pro.' means. The description is moderately transparent but not comprehensive.

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 sentence with a clear structure: a high-level phrase followed by a colon-separated list of contents. It is concise and front-loaded, but the trailing 'Pro.' adds no value and creates ambiguity, preventing a perfect score.

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 the tool's apparent complexity (40-dimension scores, stack, history), the description is too sparse. There is no output schema, no annotations, and the slug parameter is undocumented. The description does not explain how this tool relates to similar sibling tools or what 'Pro.' entails, leaving significant gaps for 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?

Schema description coverage is 0%, and the description does not mention the 'slug' parameter at all. There is no explanation of what a slug is, how to obtain it, or the expected format. The description fails to compensate for the lack of schema documentation, leaving the sole parameter completely underspecified.

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 provides a 'full demand-side profile for one company' and enumerates specific content (40-dimension readiness scores, adopted stack, per-quarter history), which distinguishes it from sibling tools like find_company_insights that search across companies. However, it lacks an explicit verb and uses the cryptic 'Pro.' suffix, preventing a perfect score.

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?

No guidance is provided on when to use this tool versus alternatives such as insights_adoption, insights_dimensions, or get_provider. The word 'Full' implies comprehensive use, but there are no explicit conditions, exclusions, or references to sibling tools.

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 must bear the full burden. It discloses that the tool returns only a top sample (not the full list), includes ranking and a total, and that view=full provides whole records. However, it does not mention authentication, rate limits, error behavior, or what 'ranked' means, leaving notable gaps.

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 with no fluff. The first sentence states the tool's core function, and the second provides the key alternative. Every word 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?

The tool is simple, but with no output schema and no annotations, the description could explain more about the response shape, the meaning of 'ranked,' and error handling. It covers the key usage alternatives and view options, making it adequate but not fully 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?

The description adds meaning to the undocumented 'slug' parameter by indicating it is an industry identifier (find_providers?industry=slug). It also reinforces the 'view' and 'limit' parameters through context about the sample and full records, adding value beyond the schema's 67% coverage.

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 that this tool returns one industry's metadata plus a ranked sample of its member providers, with the total. It explicitly distinguishes itself from find_providers (which returns the full list) and mentions the view=full alternative, making it specific and differentiated from siblings.

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 instructs to use find_providers?industry=slug for the full list, and mentions view=full as an alternative within this tool. This provides clear guidance on when to choose this tool over a sibling and how to adjust the output.

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 must disclose behavioral traits. It only states output, not whether the operation is read-only, requires authentication, or how results are ordered/limited. The 'PRO' prefix is unexplained and adds ambiguity.

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 extremely brief, which is concise, but the unexplained 'PRO' prefix and fragment structure reduce clarity. It is not structured with any additional helpful context.

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 no output schema and no annotations, the description should explain what a caller receives and any constraints. It fails to mention that results are a list, how pagination works, or any edge cases. The tool is part of a family of leader tools, but no cross-references are provided.

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?

Input schema has zero descriptions for the two parameters. The description hints that 'slug' refers to an industry vertical, but it does not explain the 'limit' parameter or how to find valid slugs. This leaves parameter usage underspecified.

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 'Top-rated providers in an industry vertical,' which clearly identifies the tool's output and domain. The name 'get_industry_leaders' further reinforces the resource. It distinguishes from sibling tools like get_area_leaders and get_region_leaders through the 'industry' keyword, though it doesn't explicitly 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 offers no guidance on when to use this tool versus alternatives such as get_area_leaders or get_region_leaders. It does not mention prerequisites, such as obtaining an industry slug via find_industries, nor when this tool is preferred.

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 members are resolved to current name, band, and score, which is useful behavioral context. However, it does not mention potential failures, authentication requirements, or the format of the returned list.

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 efficiently conveys the tool's core function and a key behavior. The 'PRO' prefix, while not essential, does not detract significantly from clarity. It is appropriately concise without being overly terse.

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 the tool has only one parameter and no output schema, the description gives a basic understanding of purpose and output. However, it omits details about the return structure, error cases, and ownership verification, making it only partially complete for an agent to use 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?

The schema has a single 'id' parameter with no description, and the tool description does not explain its meaning or format. With schema coverage at 0%, the description should compensate, but it does not mention the parameter at all. The only hint is the tool name, which implies 'id' is a list ID.

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 identifies the action ('Get') and the resource ('a list you own'), and adds a distinguishing detail: each member is resolved to current name, band, and score. This differentiates it from siblings like list_lists or create_list.

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 usage for retrieving a single owned list, but does not explicitly state when to use it versus alternatives like list_lists or get_api. The ownership qualifier ('you own') provides some context, but no direct comparison or exclusion is given.

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