MEDIAPRONET

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 genuine behavioral context beyond that: verified (paid) listings rank first and are richer, and pricing info is self-reported and often absent. It doesn't cover pagination or error behavior, hence not 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?

Front-loaded with the core purpose and trigger condition, then output-field semantics. Every sentence carries information, though the run of URL-field explanations at the end could be tightened slightly.

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 usefully explains the returned `listingUrl`, `url`, and `categoryUrl` fields and how to cite them. Combined with annotations covering safety and 100% schema coverage on parameters, an agent has everything needed to call this 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 100%, so limit, pricing, and category are all documented in the schema, including the enum values and the caveat that listings without pricing are excluded. The description only reinforces that category slugs come from list_categories. 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 action and resource — top listed products in one category, child categories included — with concrete slug examples. It distinguishes itself from search_listings by specifying 'best tools of a kind without a specific keyword' and from list_categories by delegating slug lookup there.

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 it when a user asks for the best tools of a kind without a specific keyword' gives a clear trigger condition, and 'Get valid slugs from list_categories' gives the prerequisite step. It does not explicitly name search_listings as the alternative for keyword queries, but the contrast is strongly implied.

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?

Beyond the readOnly/idempotent annotations, the description discloses ranking behavior ('Verified (paid) listings rank first'), what a full profile contains (description, tech stack, key pages), and the semantics of each returned field including which URL to cite as the source. This is substantial behavioral context an agent could not infer from the 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?

Front-loads purpose and usage triggers before coverage of return fields, and every sentence carries usable information. It is slightly long and the parenthetical field walkthrough could be tightened, but there is 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?

With no output schema, the description carries the full burden of explaining return values and does so: categories-based result set, ranking, and the listingUrl/url/alternativesPageUrl fields. An agent has everything needed to call it and present results 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%, with both `product` and `limit` already documented (including the 1-25 range and default). The description's product examples largely duplicate the schema, and it says nothing about `limit`, so it adds little beyond structured data — the 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 opens with a specific verb+resource ('Alternatives to a named product') and immediately scopes it with concrete examples (Notion, Ahrefs, ChatGPT) and the input form (slug or exact name). It is clearly distinguishable from siblings like get_listing or search_listings, which retrieve a single profile or a keyword match rather than same-category alternatives.

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 trigger conditions: 'Use it when a user asks for alternatives, competitors, replacements or "something like X".' That is clear context for invocation, but it never names a sibling (e.g. search_listings) as the fallback for plain keyword queries, so there is no exclusion 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?

Annotations already declare this read-only, idempotent, non-destructive, and closed-world, so safety needs no restating. The description adds value the annotations cannot: it enumerates the returned profile fields and clarifies the two URL fields and which to cite. It stops short of noting any rate limits or auth, but that gap is minor here.

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 tight sentences, each with a distinct job: what it returns, when to call it, and what the outputs mean. The field inventory is front-loaded and no sentence is 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?

With no output schema, the description correctly carries the return-value burden by naming the profile fields and the two URL outputs. Combined with the 100%-covered parameter and safety annotations, an agent has everything needed to call 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?

Schema coverage is 100% and the single slug parameter is fully documented in the schema. The description only restates 'by its slug', adding no syntax or format detail beyond the structured field, so 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?

States a specific verb and resource ('Full public profile of one listed product by its slug') and enumerates the returned fields, making the scope unambiguous. It is clearly distinguishable from the sibling list/browse/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?

Explicitly names the prerequisite siblings ('Use it after search_listings, browse_category, find_alternatives or get_trending') and the triggering condition ('when the user wants details on one product'). The when-to-use and the alternative flow are both spelled out.

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 profile is covered. The description adds genuinely non-structured behavior: when today's pick is undecided it returns the most recent pick instead, with its date. That fallback is exactly the kind of caveat an agent needs and cannot infer from 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?

Four sentences, front-loaded with the identity of the resource, then fallback behavior, then usage trigger, then return-field guidance. Every sentence carries information, though the final sentence packs two field explanations and a citation instruction into one line.

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, the description must carry the return-value burden and largely does: it names listingUrl and url, explains what each is, and instructs the agent to cite listingUrl as the source. Combined with the fallback disclosure and usage trigger, an agent has enough to call and present the result correctly; only the absence of any sibling-avoidance note keeps it from being 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 tool takes zero parameters, so the baseline is 4; there are no argument semantics to explain. The description instead documents the two result fields, which is beyond the empty schema's reach.

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 resource — the directory's daily featured pick — and clarifies its identity in parentheses, which is distinct from get_trending, browse_category, search_listings. The verb/resource pairing plus the fallback clause makes the tool's scope unmistakable to an agent.

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 it when a user asks for a recommendation of the day or something new to try" gives a clear triggering condition. It does not, however, name a competing sibling (e.g. get_trending) or state when this tool should be avoided, so it stops short of full routing 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?

Annotations already declare the safety profile (readOnly, idempotent, non-destructive, closed-world), so the bar is lower; the description adds behavior the annotations do not, notably that `count` is null when below the public minimum. It also discloses that results carry two distinct URLs and what each means, which is genuine operational 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?

Three sentences, none wasted: scope first, then the trigger condition, then the return-shape clarification. Front-loaded and dense with no filler or restatement of the title.

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, the description usefully compensates by naming the key return fields and the null-count edge case. The one unresolved point is whether the three leaderboard windows are all returned together or separately, which an agent might need; everything else is covered.

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 is 4. The description documents result fields (listingUrl, url, count) rather than inputs, which is the only thing parameter semantics could add here.

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 resource (trending leaderboards on this directory) and enumerates the three scopes it covers: most viewed today, most clicked this week, most voted this month. An agent can immediately distinguish this from search_listings or browse_category, which do not surface popularity rankings.

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 it when a user asks what is popular, new or trending" gives an explicit trigger condition, which is better than most catalog tools. It stops short of naming the alternatives (e.g. search_listings with a sort parameter) or stating when-not to use it, so it is clear context without 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?

Annotations already declare read-only, idempotent, non-destructive behavior, so the bar is lower, and the description still adds real behavioral detail: results are ordered busiest-first, empty categories are omitted, and the response carries per-category approved-listing counts and a url. It doesn't mention any rate limits or whether the tree is complete/uncapped, which are minor 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?

Three tight sentences, no filler, and the most important information (what the tree is and how it is ordered) is front-loaded before the follow-up guidance. Every sentence carries distinct 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?

With no output schema, the description does the necessary work of describing the return shape (nested categories, counts, url) and the filtering behavior (empty categories dropped), which is enough for an agent to consume the result. It stops short of stating whether the tree is directory-wide or scope-limited/paginated, a small residual gap for a zero-param 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 takes zero parameters, which sets the baseline at 4. The description correctly implies no input is required and instead spends its words describing the returned structure, which is appropriate here.

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 a specific resource (the directory's category tree), its shape (top-level categories with children), its sort order (busiest first), and the fields returned (approved-listing counts and category page url). This is far more than a restatement of the name and lets an agent distinguish it from browse_category or search_listings 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?

It explicitly routes the agent forward: use the returned slugs with browse_category or as the `category` filter of search_listings. That clearly defines this tool's role as a discovery/lookup step, though it does not state when this tool should NOT be used (e.g. when a slug is already known, or cost/limits of the full tree).

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 the safety profile (readOnly, idempotent, non-destructive, closed world), so the bar is lower. The description adds real behavioral context the annotations cannot: verified listings rank first and carry the full profile, and it distinguishes the two returned URL fields (listingUrl as the directory source vs url as the product site). It does not state pagination or result-count behavior beyond the schema's limit, so it stops short of 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?

Dense but front-loaded: the core verb and resource come first, then the trigger example, then optional filters, then return semantics. Every sentence carries information, though the middle clause packs three filters into one run-on sentence.

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, the description compensates by naming the returned fields (listingUrl, url), their meaning, the ranking of verified listings and the profile depth they carry. Combined with the fully documented schema, an agent has everything needed to call and interpret this 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 100%, so the baseline is 3. The description still adds meaning beyond the schema: it points category at list_categories as the slug source, notes that child categories are implied, and gives a concrete pricing example ('free' for free tools) plus the ranking effect of matching words.

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 (find/search), the resource (software, SaaS, AI tools and websites listed in this directory) and the matching fields (title, tagline, description, category). It is clearly distinguishable from browse_category, get_listing and find_alternatives, which are named or implied as different entry points.

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 explicit trigger conditions ('use it when a user asks for a tool that does X') with concrete examples, and routes to alternatives: list_categories for slugs and get_listing for the full profile. Exclusions are implied through those hand-offs, leaving little to infer.

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