Descovo

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

Discloses important behavioral traits: params structure (body/path/query), API key auto-injection, and return format. With no annotations, the description carries the full burden and does so well, though it could mention that side effects depend on the 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?

Description is well-structured with a main line and bulleted notes. It is concise and front-loaded with the purpose, though the 'Args' section could be integrated more succinctly.

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 generic nature and presence of an output schema, the description provides adequate context about API key handling, parameter structure, and references to sibling tools. It is complete enough for an agent to use 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?

Despite 0% schema coverage, description explains the params structure as a dict with body/path/query keys and defines operationId as the operation ID. This adds necessary meaning beyond the schema's bare types.

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 the tool executes any Descovo API operation by operationId, with a specific verb and resource. Differentiates from sibling tools like search_endpoints and get_endpoint_details_full.

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 instructions: prefer search_endpoints when choice is ambiguous, use get_endpoint_details_full for complex parameters, and notes API key handling. This helps agents decide when to call this tool vs 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 full burden. It discloses that the tool returns 'Complete schema including all required/optional fields, request body schema, response schema, and example usage.' This is transparent about the read-only nature and return value.

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 a few sentences with a clear structure (Args, Returns). Every sentence adds value, and it is front-loaded with purpose.

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 an output schema exists, the description sufficiently covers what the tool does and what it returns. No gaps for the agent to infer.

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%, but the description explains the parameter 'operationId' with an example ('syncContactEnrichment'), adding meaningful context beyond the schema type.

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 verb 'Get' and resource 'COMPLETE schema and details for a specific API operation'. It distinguishes from siblings like 'call_operation' by specifying it should be used before calling an API.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says 'Use this BEFORE calling an API to understand exactly what parameters are needed.' This provides a clear usage context, though it lacks explicit when-not-to-use 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 provided, so description carries full burden. It does not disclose pagination behavior, rate limits, or output structure (e.g., whether it returns IDs or full details). Only mentions optional filtering.

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?

Single sentence is concise and front-loaded. No wasted words, though structure could be enhanced with bullet points for 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?

With 4 optional parameters and an output schema, the description is too minimal. It does not explain parameter interactions or what the output contains, leaving the agent to infer.

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 has 0% description coverage. Description mentions 'tag/search filtering' covering 'tags' and 'search' but does not explain 'limit' or 'tagPack' parameters. Adds partial meaning but insufficient.

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 verb 'list' and resource 'Descovo API endpoints' with optional filtering. It distinguishes from siblings like 'get_endpoint_details_full' (details) and 'search_endpoints' (search), but does not explicitly differentiate from the search tool.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives like 'search_endpoints'. No exclusions or context about when listing without filters 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 only restates the name and a vague purpose, with no disclosure of return format, rate limits, or other behavioral traits beyond listing.

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, front-loaded with the core action. Every sentence adds value: first states what it does, second gives usage 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?

Adequate for a simple parameterless list tool with an output schema (not shown). However, it could elaborate on what tag packs are and what the output contains, leaving some gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters and schema coverage is 100% by default. Description adds no param info, but baseline is 4 for no 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 the tool lists curated tag packs for large tool catalogs, and provides an example use case ('social-media or enrichment'). It effectively distinguishes from sibling tools like list_all_endpoints and search_endpoints by focusing on tag-based exploration.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says 'Use this to narrow exploration' with examples, implying when to use. However, it does not specify when not to use or alternatives, though the sibling names suggest other options.

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 states the tool is for discovery and ranking, implying a read-only operation, but does not explicitly say it has no side effects. It mentions optional constraints and tag-scoped selection, which provides some behavioral context but lacks explicit safety traits.

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 sentences: first defines the role, second gives usage guidance, third lists capabilities. It is front-loaded and every sentence adds value with 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?

The description adequately explains the purpose and tag-scoping but does not explain the query or constraints parameters. The existence of an output schema reduces the need to describe return values, but the description should still cover how to use the basic query input.

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%. The description only explains tag-related parameters (preferredTags, excludedTags, tagPack) but does not explain limit, query, or constraints. For a 6-parameter tool, this partial coverage leaves significant gaps.

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 is the 'Canonical API selection tool for endpoint discovery and ranking' and instructs to 'Use this first to get the top recommended operations for a user intent.' It distinguishes from siblings like call_operation and get_endpoint_details_full by positioning itself as the initial selection 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?

The description explicitly says 'Use this first', giving clear context on when to use. It does not provide explicit when-not-to-use or alternatives, but the context of being the canonical selection tool implies it should be used before other tools.

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