AI Agents Listing

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

No annotations are provided, so the description carries the disclosure burden. It implies a read-only comparison and discloses the 2-5 item cardinality, but says nothing about behavior on unresolvable/duplicate slugs, ordering of results, or failure modes. Adequate for a simple read, but not rich.

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: what is compared and on which fields comes first, the slug prerequisite second. Zero filler and nothing redundant with the schema.

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 one-parameter tool with no output schema, enumerating the compared fields effectively communicates what comes back, and the pre-resolution guidance covers the main failure mode. Minor gaps remain around result ordering and handling of invalid slugs.

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 0% and the single 'slugs' parameter has no schema description, so the description must compensate — and it does: it explains the parameter is a list of listing slugs, constrains it to 2-5 items, and tells the agent where to source valid values. Only the format/validation of individual slug strings is left unstated.

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 ('Compare 2-5 listings side by side') plus the exact comparison dimensions (pricing, access model, categories, heat, upvotes, rating). The multi-listing scope distinguishes it from get_listing, and the metric list makes the operation concrete rather than generic.

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 path: slugs must first be obtained via search_listings or find_alternatives. That is real routing guidance against siblings. It stops short of an explicit when-not-to-use rule (e.g. 'use get_listing for a single listing'), so it is not a full 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?

No annotations are provided, so the description carries the full burden. 'Browse' implies a non-mutating read against a directory, which is useful, but it says nothing about result ordering defaults, limits, or what an empty browse returns.

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, zero waste, with the capability statement front-loaded and the disambiguating condition plus examples immediately after.

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 seven parameters, low schema coverage and no output schema, an agent still lacks a picture of the result shape and how sort/limit interact with browsing. The facet coverage is decent but partial.

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 only 29%, and the description covers four of seven facets (vertical/industry, category, pricing, access model). It adds no guidance on sort, limit, or type, which are undocumented or enum-only in the schema.

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 ('Browse') plus resource ('the directory') and the facets being filtered. The second sentence implicitly separates it from name-based search, so an agent can distinguish it from 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?

Gives an explicit use condition ('when the ask is a kind of product rather than a name') backed by two concrete example queries. It does not name search_listings as the alternative for name lookups, so routing is implied rather than 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, the description carries the full burden. It usefully discloses that products outside the directory are handled by returning closest topic-based listings, which is meaningful behavior beyond the schema. However, it says nothing about permissions, rate limits, result shape, or whether the limit parameter truncates results.

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 compact, front-loaded with the core purpose, and every clause adds information. It could be organized slightly more clearly, but there is no padding.

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 two-parameter retrieval tool with no output schema, the description explains accepted input forms and fallback behavior but leaves gaps around return values and the role of the limit parameter. An agent can invoke it, but cannot fully predict the response shape.

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 50%, so the description must compensate. It does well for the 'product' parameter by explicitly listing slug, URL, or name and explaining the out-of-directory fallback. It adds no semantic meaning for 'limit' beyond what the schema's default and bounds already convey.

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 resource, alternatives and competitors for a given product, which is clearly distinct from sibling tools like search_listings, compare, or get_listing. It does not explicitly name or contrast with those siblings, keeping it just short of a 5.

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 purpose implies usage (find competitors for a product), but there is no explicit when-to-use or when-not-to-use guidance relative to alternatives such as search_listings or discover. The fallback note is more behavioral than a usage rule.

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 behavioral burden. It usefully states that only 'published' listings are returned and that the response includes description and links, but it does not mention permissions, error behavior for missing/unpublished slugs, or rate 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 a single front-loaded sentence with no wasted words. It states the action, scope, identifier, and return contents efficiently.

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 one-parameter read tool with no output schema, the description is nearly sufficient: it explains scope, identifier, and return payload. It leaves out edge-case behavior such as not-found or unpublished responses, but that is a minor gap given 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?

Schema description coverage is 0%, so the description should compensate. It identifies the parameter as a 'slug', which gives semantic meaning, but adds no format, example, or constraint details beyond what the schema already provides.

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 — 'Fetch one published listing by its slug' — and clarifies what is returned: full description and links. It is clear enough to distinguish from list/search siblings, though it does not explicitly name an alternative 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 phrase 'by its slug' implies the tool is used when the slug is already known, but there is no explicit guidance on when to use this versus search_listings or other siblings. The usage context is implied rather than 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?

No annotations are provided, so the description carries the full burden. It conveys that this is a lookup that returns ids, but says nothing about whether the result is stable/paginated, whether auth is needed, or how large the list might be. Adequate for a simple read, but not rich.

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 short sentences, front-loaded with the purpose and followed by the actionable ordering constraint. 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?

For a single-optional-param read tool with full schema coverage and no output schema, the description covers what it returns (ids) and the sequencing constraint. Only minor gaps remain, such as behavior of the optional type filter.

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% and the single optional `type` parameter is an enum fully documented in the schema, so baseline 3 applies. The description does not mention the vertical filter at all, so it adds nothing beyond the schema.

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 (list category ids) and scopes it to what a submission can be filed under, which distinguishes it from search_listings and discover. It also clarifies the return shape (ids, not names), which is the key distinction an agent needs.

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 and the follow-on tool: call this before submit_listing. It also explains why (submit_listing takes ids, not names), removing any ambiguity about whether this step can be skipped.

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 behavioral burden and does not meet it. It doesn't say whether this is a read-only listing operation, whether results are ordered, whether pagination exists, or what the response contains.

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?

It is a single short sentence with zero waste and the recency scope is front-loaded. Brevity here reflects under-specification rather than efficient communication.

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 annotations, no output schema, an undocumented 'limit' parameter, and several overlapping siblings, the description should do considerably more work. An agent cannot reliably decide between this and 'trending' or 'discover' from what is given.

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 50%: 'days' is documented but 'limit' has no description anywhere. The description does not compensate — it mentions recency but gives no detail on the lookback window default, bounds, or result-count behavior.

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 the resource (listings) and the scope (most recently published), which is more than a restatement of the name. However, it carries no verb and gives no basis for distinguishing this from siblings like 'trending' or 'discover', which likely also surface recent or noteworthy listings.

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 use this tool versus 'trending', 'search_listings', or 'discover'. The only implicit cue is recency, which the agent must infer from the name and description alone.

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 does add one real behavioral fact — only *published* listings are returned — which implies a read-only, scoped retrieval. But it says nothing about ranking/relevance ordering, whether matching is substring or tokenized, pagination behavior, or what an empty result looks like.

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 well-formed sentence with no filler, and the resource scope is front-loaded. It earns nearly every word, though it leaves little room for the usage and result-shape guidance an agent would want.

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?

There is no output schema and no annotations, so the description is the only place to learn what comes back. It covers what is searched but not the result shape (summaries? full listings?), relevance ordering, or the limit cap's effect — meaningful gaps for a directory search 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 description coverage is 67%: query and type are documented in-schema, while limit has only default/min/max constraints. The description's mention of name/tagline/description largely restates the query field description, and listing the three content types adds little over the enum. 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 (search) and a specific resource (published AI agents, MCP servers, skills in the directory) and names the fields matched. It's clear what the tool does, but it doesn't differentiate itself from siblings like discover, find_alternatives, or trending that could plausibly be used for similar lookup intents.

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 word 'search' plus a required free-text query signals keyword lookup as opposed to browsing. There's no explicit guidance on when to pick this over discover, find_alternatives, trending, or new_launches, and no exclusions are 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, the description carries the full burden and does well: it discloses the pending-review queue outcome, an auth prerequisite plus the sign-in escape hatch, and the important non-obvious side effect that a duplicate URL mutates the existing listing's submitter details rather than creating a new record. It omits what the response looks like beyond the URL.

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 short sentences, front-loaded with the action and then layering outcome, duplicate behavior, and auth. Every sentence carries information; only the auth sentence is slightly self-referential in a way that reads awkwardly against 'requires an authenticated connection'.

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 covers outcome, duplicate handling, and auth, which is most of what an agent needs. But for a tool that claims to submit a product while exposing zero input parameters, the description never explains how the product is actually specified, leaving a real gap in invocation understanding.

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 has zero parameters, so there is nothing for the description to disambiguate; baseline applies. The description does add that the return value is a URL for finishing/tracking the submission, which is value beyond the empty schema.

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 ('Submit a product to the directory') with the actor scoped ('on behalf of the connected user'). It is clearly distinguishable from get_listing/search_listings, though it doesn't explicitly differentiate itself from the closest sibling, submit_review.

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 a clear condition for calling (submitting a product for the connected user) and a useful invocable fallback ('call this tool to get the sign-in instructions' when unauthenticated). It does not name alternatives or state when not to use it.

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 and does most of it well: it discloses upsert semantics (repeat calls update), the per-account/per-listing uniqueness constraint, that the review becomes publicly visible and is labeled agent-submitted, and that an unauthenticated call returns sign-in instructions rather than failing opaquely. Missing only finer points like moderation/delay or whether a review can be withdrawn.

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, front-loaded with the purpose, then the uniqueness/update rule, then the auth requirement. The auth sentence slightly restates the title's "sign-in required" but adds the useful hint about how to obtain instructions.

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 critical unknowns — auth path, side effect visibility, and idempotent update behavior. The remaining gap is the argument shape, since the schema declares no properties at all and the description only describes them narratively.

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 is empty (zero properties), so the description is the only source of input semantics, and it does supply the rating range (1-5) and the optionality of the note. However, it never names the actual field keys or how to encode the rating versus the note, leaving an agent to guess the argument shape for a tool that evidently accepts data.

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?

Names a specific verb and resource ("leave a review on a listing") and spells out the payload conceptually (1-5 star rating, optional note). It is unmistakably distinct from every sibling in the set (search_listings, get_listing, submit_listing), so an agent can route here without ambiguity.

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?

States the key usage condition — one review per account per listing, calling again updates the existing one — which resolves the create-vs-update question an agent would otherwise guess at. It also flags the sign-in prerequisite up front, though it doesn't explicitly warn against using it for non-review submissions (that is submit_listing).

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?

In the absence of annotations, the description details the behavioral trait of ranking based on 'heat (the 0-100 engagement score).' This adds crucial context about how the data is calculated beyond the simple list functions of sibling tools.

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 highly efficient. It is composed of three sentences, and the key information—ranking criteria and paid listing exclusion—is front-loaded for immediate agent understanding.

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 low complexity (3 parameters, no output schema), the description is fully complete. It covers the definition of the ranking mechanism and the crucial business rules regarding paid listings.

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 schema coverage being 67%, the description adds significant semantic value. It explicitly defines 'heat' as a '0-100 engagement score' and specifies that the results are measured over a 'rolling window,' enriching the context of the parameters beyond their basic 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?

The description clearly defines the tool's purpose as listing 'Listings gaining momentum right now.' It explains that the listings are ranked based on metrics like heat, upvotes, or reviews, effectively distinguishing it from generic listing 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?

The description provides a critical usage constraint by stating that paid listings do not have a ranking preference. It clarifies the role of the 'featured' flag, offering necessary context for usage that would otherwise be ambiguous.

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