toolradar

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

Annotations already declare readOnly, idempotent, non-destructive, and closed-world, so the safety profile is covered. The phrase 'computed insights' hints that the tool does more than return raw records, but it never says what those insights are or how the comparison is derived, and no invalid-slug behavior is described.

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 front-loaded sentence with no filler. Brevity is a virtue here, though it comes at the cost of any guidance beyond the core 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?

With an output schema and full annotations, the description needn't explain return values or safety. Still, for a comparison tool the description omits what dimensions are compared and how to handle unknown or duplicate slugs, leaving meaningful 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?

There is one parameter with 0% schema description coverage; the schema only says 'array of strings'. The description clarifies that the entries are tool identifiers ('tools') and that 2-4 are required — though the count range merely restates minItems/maxItems already in the schema. Adequate but thin for a zero-coverage parameter.

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 ('Compare') and resource ('tools') plus the accepted cardinality ('2 to 4 ... side by side'). It clearly differs from single-tool siblings like get_tool and from search_tools, though it never names an alternative explicitly.

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

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

Usage is only implied by the verb — nothing says when to prefer this over get_tool, get_alternatives, or recommend_tools, nor what precondition (e.g. needing multiple known slugs) makes it the right choice. An agent must infer the routing decision entirely.

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?

The annotations already declare readOnlyHint, idempotentHint, non-destructive behavior, and openWorldHint=false. The description adds useful context that results are 'real, AI-identified' direct competitors rather than category matches, but it does not describe result freshness, ordering, or limitations beyond that.

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 tight sentence with the core distinction front-loaded. There is no filler or repetition, and the parenthetical earns its place by narrowing the 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?

An output schema exists, so return values need not be explained, and annotations cover the safety profile. However, the description leaves the required slug parameter and the relationship to sibling tools underspecified, so it is only minimally complete for an agent selecting and 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?

Only the limit parameter has schema description coverage (default 10, max 20). The required slug parameter is undocumented in both schema and description, and the description does not clarify its expected format or whether it is a tool identifier. With 50% schema coverage, the description does not compensate for 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 states a specific verb and resource: 'Get ... alternatives to a tool.' The parenthetical clarifies that these are direct competitors rather than category matches, which distinguishes it from broad category-oriented siblings, though it does not explicitly name compare_tools or recommend_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?

Usage is implied by the 'direct competitors, not category matches' exclusion, but the description does not explicitly say when to use this tool versus compare_tools, recommend_tools, or search_tools. There is no guidance on limits or when one alternative tool should be 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?

Annotations already cover read-only, idempotent, non-destructive, closed-world behavior, so the description's added value is telling the agent prices carry provenance and a verification timestamp—i.e., data can be dated and should be attributed. That is genuine context beyond the annotations, though it does not discuss what happens when no pricing exists.

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 with no waste; the purpose and the provenance fields are front-loaded ahead of the quoting instruction.

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 an output schema present, the description need not enumerate return values, and annotations cover safety. The remaining gap is minor: the meaning/format of slug and behavior on missing pricing are left unaddressed.

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?

Only one parameter (slug) with 0% schema description coverage; the description implies the slug identifies a tool but never states the accepted format or whether it matches get_tool's identifier. The gap is small given the single parameter, but the description does not fully 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?

Specific verb+resource ('Get a tool's pricing') plus a summary of what the response carries (lastVerifiedAt, sourceUrl, confidence). It is clear what the tool does, though it does not explicitly contrast itself with siblings like get_tool or compare_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?

'Cite the verification date when quoting a price' is guidance on how to use the output, not when to call this tool instead of compare_tools or get_tool. There are no exclusions or preconditions, so usage is only implied by the name.

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 already declare readOnlyHint, idempotentHint, and openWorldHint=false, so safety behavior is covered. The description adds value beyond that by disclosing the toolradarData structure and the citableSentence field explicitly meant for quoting with its date, which is a behavior an agent could not infer from annotations. No contradiction with annotations.

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 dense sentences, front-loaded with the core action, then the return payload, then the fallback instruction. Every clause carries information; nothing is redundant.

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?

An output schema exists, so return values need not be fully re-explained, and the description still highlights the non-obvious citableSentence field. Combined with the search_tools routing hint, an agent has everything needed to call this 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% for the single 'slug' parameter, so the schema gives no format guidance. The description compensates partially by saying the lookup is 'by slug' and that slugs come from search_tools, but it does not specify slug format or where to find the slug in search results.

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 and resource ('Get full detail for one tool by slug') and then enumerates exactly what comes back: description, pricing, pros/cons, features, score, review synthesis, and toolradarData. This distinguishes it clearly from siblings like get_pricing and get_alternatives, which return narrower slices.

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?

Gives an explicit routing rule: 'Use search_tools first if you do not know the slug.' That is a real when-to-use condition naming the alternative. It stops short of exclusions (e.g., when to prefer get_pricing or compare_tools over this broader call), so not quite 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?

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety and side-effect profile is fully covered. The description adds only the scope note that the list is limited to categories 'Toolradar tracks', which is mildly useful but nothing beyond the structured data. No mention of result size, ordering, or whether the list is 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?

A single short sentence with no filler, front-loading the verb and resource immediately. 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 zero-parameter, read-only enumeration tool with full annotations and an output schema, the description covers the essentials and need not describe return values. The only minor gap is not hinting at what the categories are used for downstream (e.g., as filter values in search_tools).

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 takes zero parameters, so the baseline applies and there is nothing for the description to disambiguate. No parameter-related omissions exist.

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 gives a specific verb and resource ('List the software categories Toolradar tracks'), which is unambiguous about what the tool returns. It is implicitly distinct from the tool-centric siblings (search_tools, get_tool, compare_tools) since none of them return categories, but it doesn't explicitly state that distinction.

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 call this versus the sibling tools. An agent could reasonably infer it is a discovery/enumeration call, perhaps to obtain valid category values for filtering, but that is left entirely to 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?

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds non-obvious output behavior — that each recommendation carries a rationale, fit_score, caveats and a verified price — which tells the agent what quality bar to expect. Missing only operational details like result latency or whether sourcing is live.

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 filler, with the capability stated first and the sibling routing second. 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?

An output schema exists, so return format needs no explanation, and the annotations carry the safety profile. With 7 parameters at 71% coverage, a couple of bare parameters (team_size, pricing) remain unstated, but the required parameter and the core intent are fully clear.

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 71%, so most parameters are already documented in the schema, and the description's one worked example ('simple CRM for a 6-person agency that syncs Gmail') mirrors the schema's own need example rather than adding new meaning. Undescribed parameters like team_size and pricing are not clarified in prose. Baseline 3 is appropriate.

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

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

States a specific verb and resource ('Recommend the best tools for a described need') and immediately qualifies the output shape ('justified, sourced shortlist'). It is clearly separable from search_tools and get_alternatives without opening a schema.

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 the alternative (search_tools) and the exact condition that selects this tool: the user describes a goal or constraints rather than a keyword. This is the when-to-use/when-not pattern at full strength.

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 already declare the write/safety profile (readOnly=false, destructive=false, openWorld=false, non-idempotent), so the description's real contribution is telling the agent this files into a 'verification queue' — implying human review rather than an immediate fix. It does not say what happens after review or whether duplicate reports are merged, which would complete the picture.

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, front-loaded with the action and destination. There is slight redundancy between the parenthetical examples and 'when our data looks wrong', but nothing is wasted at length.

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 an output schema present, return values need no explanation, and annotations cover safety. The description is complete enough to call the tool correctly; only post-submission behavior (queue turnaround, deduplication) is left out.

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 75%, so the schema carries most of the burden. The description's issue examples loosely map to the 'pricing'/'status'/'feature' enum values, adding some interpretive value, but it says nothing about the 'claim' or 'evidence_url' 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?

States a specific verb and resource ('Report a data problem') and gives concrete examples (wrong price, dead tool, missing feature), plus the destination ('Toolradar verification queue'). It is clearly distinct from the read-only siblings like get_tool or compare_tools, though it never names 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?

'Use this when our data looks wrong so we can fix it' gives an explicit trigger condition, and the examples sharpen it. No exclusions or named alternatives are offered, but for a single intake tool among pure lookups there is little ambiguity to resolve.

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 already establish readOnly, idempotent, non-destructive, and closed-world behavior, so the safety profile is covered. The description adds genuinely useful context the annotations don't carry: catalog scale, the exact fields returned, and a citation obligation when quoting prices. It omits pagination behavior beyond the limit param, keeping it from a 5.

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 compact sentences, with the core purpose front-loaded. The final citation sentence is an operational requirement rather than a description of the tool, but it does earn its place by preventing unattributed price quoting.

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?

An output schema exists, so return values needn't be explained and the description only sketches them briefly. With zero required parameters and annotations covering safety, the definition gives an agent enough to invoke correctly; only the sibling-routing guidance is missing.

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

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

Schema description coverage is 80%, so the schema already documents query, category, limit, and sort adequately. The description adds no parameter-level detail — notably the bare 'pricing' enum has no description in either place. Baseline 3 applies when the schema does the heavy lifting.

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 (search/filter) and resource (software tools) and quantifies the catalog at 10,000+ tools, which is more informative than the title. It stops short of distinguishing itself from siblings like get_tool or recommend_tools, so an agent still has to infer which entry point fits a given request.

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 only implied — the description says what searching does but never states when to pick this over recommend_tools, compare_tools, or get_tool. There are no exclusions or prerequisites, so the agent must derive selection logic from the sibling names alone.

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