WireTensors

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

No annotations are provided, so the description carries the burden. It discloses the nature of the result (side-by-side details with specific comparison categories) and implies a read-only comparator, but it does not describe error behavior, response format, or what happens for invalid/missing slugs.

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 no filler. It states the primary purpose, the input mechanism, and the output categories efficiently, earning every word.

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 comparator, the description covers purpose and key output fields, but with no output schema or annotations it leaves response structure, edge cases, and failure behavior unspecified. 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 description coverage is 0%, so the description must compensate. 'By slug' gives both slug_a and slug_b meaningful semantics as tool identifiers, but it does not specify slug format, case sensitivity, or whether the slugs must correspond to existing tools.

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 a specific action ('Side-by-side detail') and resource ('two tools by slug'), and enumerates the comparison fields (pricing, rating, pros/cons, best-for/avoid-if). It distinguishes itself from siblings by requiring two slugs, unlike search_tools, get_tool, recommend_tool, or list_categories.

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

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

The description gives a clear use context: compare two known tools by slug. It does not explicitly mention when not to use it or name alternatives such as get_tool for single-tool details, but the two-slug requirement makes the intended scenario evident.

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

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

Annotations are absent, so the description must carry the full burden of behavioral disclosure. It states it returns 'Full review detail' but does not specify the structure, whether it is read-only, or any side effects. For a GET-like tool, this is minimal; an agent would not know what fields to expect or if any permissions are needed.

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 with no filler. It front-loads the core purpose ('Full review detail for a single tool') and then provides the input source, making it efficient and easy to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with one parameter and no output schema, the description covers the purpose and parameter source, but lacks detail on the return format or any behavioral specifics. It is adequate for basic invocation but leaves the agent guessing about the structure of the 'full review detail' response.

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 documents the slug parameter with an example. The description adds context by noting the slug comes from search_tools results, which clarifies the expected source. This adds value beyond the schema's type and description, so it earns a slightly above-baseline score.

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 'Full review detail for a single tool' by its slug, which is a specific verb and resource. It distinguishes itself from search_tools by referencing that the slug comes from search_tools results, implying this tool is for retrieving details of one item rather than searching. However, it does not explicitly name a sibling alternative, so it lacks the full differentiation of a top-tier 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?

The description implies a workflow: first use search_tools to obtain a slug, then use this tool for full details. This gives some usage context but does not explicitly state when to prefer this tool over siblings like compare_tools or recommend_tool, nor does it mention when not to use it. The guidance is present but implicit, not 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 must disclose behavior, but it does not. It gives no information about output, side effects, ordering, pagination, or error cases. The garbled sentence about grouping on WireTensors is not a behavioral description.

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 it is under-specified and grammatically broken ('grouped into on WireTensors'). Brevity here does not serve clarity; it reads more like an accidental fragment than a deliberately concise definition.

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 and an output schema, the description should explain what the tool returns and what 'categories' refers to. It does neither, so an agent cannot predict the tool's output or understand the WireTensors context beyond the title.

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

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

The tool has zero parameters, so there are no parameter semantics for the description to clarify. The empty input schema is therefore complete for invocation purposes, matching the baseline for a no-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 title 'List tool categories' conveys the intent, but the description only says 'All categories tools are grouped into on WireTensors,' which is a fragmented, unclear restatement of the category concept. It never explicitly states that the tool lists categories, and it does not differentiate the tool from siblings like search_tools or get_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?

There is no guidance about when to use list_categories versus the sibling tools. The description does not mention scenarios, exclusions, or alternatives, leaving the agent to infer usage purely from the tool name and title.

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 at all, the description carries the transparency burden and does disclose key behavior: it filters by category/budget/free-tier and ranks by WireTensors rating. It does not mention rate limits, output shape, or pagination, but for a read-only recommendation tool those omissions are minor.

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 dense sentence that front-loads the purpose, provides a concrete example, and includes the filtering and ranking mechanism without any 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 an all-optional-parameter, read-only recommendation tool, the description plus schema covers most invocation needs. The main gap is that `limit` is undocumented and there is no output schema, so the exact returned shape is left implied.

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 40%, so the description needs to compensate. It adds semantics for category and free_tier and the example maps budget/category usage, but `limit` is never explained, leaving a key aspect of the ranked response 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?

States a specific verb ('Get') and a specific outcome ('a ranked recommendation'), with a concrete example. It distinguishes itself from siblings like search_tools and compare_tools through the ranked-recommendation angle.

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?

Clearly states the usage context: use when a user wants a ranked recommendation filtered by category/budget/free-tier. It does not explicitly name alternative siblings or give a when-not-to-use statement, so it misses the top tier.

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 must carry the full burden of behavioral disclosure. It states that results are ranked by rating and include pricing, rating, and links, which is useful. However, it does not disclose default behavior when no filters are given, whether pagination exists, or any rate limits. It is adequate but not exhaustive.

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 primary purpose and result format, then a pointer to get_tool. No wasted words, highly efficient.

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 explains the output includes a ranked list with pricing, rating, and links, and the schema covers all parameters. It lacks details on default limits, behavior when no filters are applied, and how multiple filters combine, but for a search tool with a clear schema, 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?

Schema description coverage is 100%, so all parameters have descriptions in the schema. The description does not add additional meaning to parameters, only refers to 'given filters' generically. Thus it meets the baseline for schema coverage but does not go beyond.

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 searches and filters the tool catalogue, returns a ranked list with specific fields (pricing, rating, links), and explicitly distinguishes itself from get_tool which provides full detail. This gives an agent a precise understanding of the tool's function and differentiates it from a sibling.

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 get_tool as the alternative for full detail, providing clear guidance on when to use this tool for search/filter versus that for details. However, it does not mention other siblings like compare_tools or recommend_tool, so the guidance is partial but sufficient for the primary 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, the description carries the behavioral disclosure burden. It gives a fair idea of the output contents, but leaves 'coverage dates' vague and does not explain the response format. The tool is simple and read-only by nature, so this level is minimally viable.

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 with no filler. It is slightly telegraphic, but every phrase maps to a distinct piece of useful 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 zero-parameter, stateless info tool, the description is mostly sufficient: an agent can infer the call needs no input. However, the absence of any usage context or output-shape hints leaves minor ambiguity around what 'coverage dates' means and how the result is presented.

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 has no need to explain parameter meaning, and it does not clutter the definition with irrelevant detail.

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

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

The description names three concrete outputs: tool count, coverage dates, and an explanation of what WireTensors is. This clearly distinguishes it from sibling tools like search_tools or compare_tools, though it lacks an explicit verb such as 'returns' or 'provides'.

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 about when to use this tool versus alternatives. The sibling context shows related tools, but the description never says 'use this for site-level metadata' or 'use get_tool for specific tool details'.

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