discovery

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 adds value by listing the fields returned (outbound url, creator, tags, popularity/recency signals), but it doesn't explicitly state that the operation is read-only or describe error behavior. The verb 'Get' implies a safe read, but the description could be more explicit about side effects and response format.

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, well-structured sentence that conveys the core function and key return fields without unnecessary words. It is concise yet informative, earning its place entirely.

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 one parameter, no output schema, and no annotations, the description adequately covers the tool's purpose and return content by naming specific fields. It doesn't mention errors or return format, but for a simple get-by-id tool, the core information is present. Slightly lacking in explicit return structure, but sufficient for the tool's simplicity.

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

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

The schema contains one required 'id' string parameter with no description (0% coverage). The description clarifies that the id refers to a listing ID, which adds meaning beyond the schema. However, it doesn't provide details on id format, source, or validation, so the addition is minimal and only partially compensates 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 is specific and clear: 'Get full detail for one listing by id' uses a strong verb and resource, and enumerates included fields (outbound url, creator, tags, popularity/recency signals). This distinguishes it from sibling tools like search_indie, which focus on searching rather than retrieving a single known listing.

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 phrase 'by id' clearly implies the tool should be used when a specific listing identifier is known and full details are needed. While it doesn't explicitly mention alternatives like search_indie or when not to use, the context is clear for a get-by-id operation. No exclusions or alternative references are provided, but the usage context is reasonably 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 are provided, so the description carries the full burden of behavioral disclosure. It describes what information is returned but does not explicitly state that the tool is read-only or side-effect-free, nor does it mention any limitations (e.g., what counts as 'fresh' or 'small'), authentication requirements, or rate limits. This is a significant gap given the lack of annotation support.

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. It front-loads the core question ('How much... is available') and then lists the key statistics. Every word earns its place; there is no filler 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?

For a zero-parameter, no-output-schema tool, the description covers the main return dimensions (totals, freshness, size, top sources/languages/tags). However, terms like 'fresh' and 'small' are undefined, and the absence of an output schema leaves the return structure unspecified. Still, it is adequate for a straightforward stats 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 tool has zero parameters and the schema is trivially complete (empty object). Per the baseline rule for zero-parameter tools, a score of 4 is appropriate. The description adds no parameter information but also needs none, as there is nothing to clarify.

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 that the tool provides an aggregate statistical overview of the independent-software index (total listings, freshness/size categories, top sources/languages/tags). It is distinguishable from sibling tools like get_listing (which fetches a single listing) or search_* (which finds specific items), though it lacks an explicit verb such as 'retrieve' or 'compute'.

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 explicit guidance is provided on when to use this tool versus alternatives. The description does not mention that this is the preferred tool for index-level statistics, nor does it exclude cases where get_listing or search tools would be more appropriate. Usage context is only implied by the content, not 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 behavior disclosure. It transparently describes what the tool returns: middleware capabilities with counts and available platforms. It does not discuss performance or side effects, but as a no-parameter listing tool, the transparency 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 two sentences: the first states what the tool lists, the second gives a direct usage instruction. Every word contributes value; there is no repetition 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?

The description fully explains the tool's output (capabilities with counts, platforms) and its role within the middleware search workflow. Since there is no output schema, this is sufficient for a zero-parameter listing 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 tool has zero parameters, so the baseline is 4. The description appropriately focuses on the output rather than inputs, and no additional parameter semantics are 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 verb ('List') and the resource ('middleware capabilities Devadex indexes'), enumerates example categories, and mentions the extra output of platforms. It further distinguishes itself by tying its use to picking values for search_middleware, which is one of the sibling tools.

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

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

The description explicitly directs the agent to use this tool to pick a capability/platform for search_middleware. It lacks a formal 'when not to use' clause, but the specific use-case guidance is clear and actionable, going beyond mere implication.

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 an important behavior: each result has a buyUrl that may be an affiliate link and is the intended link to send the user to, plus a clean url. It also explains the meaning of the small and fresh filters. This is valuable context beyond what the schema provides, though it omits other behaviors like pagination or result limits.

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 tightly written in two sentences. The first sentence states the core purpose, and the second adds crucial output details and filter usage. No filler or redundant information. It is front-loaded with the most important 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 5 optional parameters and no output schema, the description covers the essential purpose, the key result fields (buyUrl, url), and parameter semantics. It lacks full return format details (e.g., other result fields, ordering, pagination), but it is reasonably complete given the tool's apparent simplicity. The absence of an output schema makes full return shape disclosure more important, so a small deduction is applied.

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 already provides detailed descriptions for all 5 parameters (100% coverage). The description adds little beyond rephrasing the small and fresh parameters ('low-authority (buried)' vs 'recent launches'). Since the schema already handles parameter meaning, the description's contribution is minimal, warranting the baseline score of 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 opens with a specific verb and resource: 'Search independent, small, and newly launched software that mainstream search engines bury.' This clearly states what the tool does and its distinctive scope, distinguishing it from generic search tools. The mention of 'buyUrl' and 'clean url' further clarifies the output type.

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: when searching for indie/small/new software that mainstream engines bury. It also gives actionable parameter guidance ('Use small=true to see only low-authority (buried) results, fresh=true for recent launches'). However, it does not explicitly mention when not to use it or name alternative sibling tools like search_middleware.

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 that the tool returns middleware libraries, SDKs, and systems with outbound links, and explains the search is by capability across every platform. It doesn't mention error handling, pagination, or potential side effects, but as a search/read operation, the behavior is largely transparent. It adds value beyond annotations (which are absent) and covers the core return 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 a single, front-loaded sentence with an em-dash example list, followed by one sentence of parameter guidance. Every clause earns its place, with no filler or redundancy. It is compact yet packed with useful information, achieving top marks for structure and conciseness.

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, the description explains the high-level return (middleware libraries, SDKs, systems with outbound links) and parameter usage. It would be improved by noting the behavior when no parameters are provided (e.g., returns all middleware) or any pagination/ordering, but for a simple search tool, it covers the essentials. The reference to list_capabilities adds contextual completeness for the capability parameter.

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

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

Schema coverage is 100%, so the baseline is 3, but the description enriches each parameter: 'capability' is tied to an exact slug from list_capabilities, 'platform' is explained as an engine/language, and 'query' is illustrated with examples. This goes beyond the basic schema descriptions, providing cross-tool integration and usage context, justifying a 4.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool searches for reusable software middleware by capability, with specific examples (dialogue, authentication, etc.) and notes it returns libraries, SDKs, and systems with outbound links. This is a specific verb+resource+scope and, while it doesn't explicitly name siblings, the focus on middleware clearly distinguishes it from tools like search_indie.

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 parameter usage instructions: use 'capability' for the exact capability slug (referencing list_capabilities), 'platform' to narrow down, and 'query' for free text. It implies the tool is the go-to for middleware discovery across platforms, but it does not explicitly exclude alternatives or state when not to use it. This is clear context without explicit exclusions, earning a 4.

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