PublicAPIs.io

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

The readOnlyHint annotation already establishes this is a non-mutating read, and the description adds genuine value by disclosing what the comparison returns (auth, free tier, HTTPS, pricing, docs summary) and the 2-5 input bound. It does not describe output format or any rate/size limits, but for a read-only compare that is a minor gap.

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 filler. The operation and its scope are front-loaded, with the prerequisite tucked into a short second 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?

For a single-parameter, read-only tool with no output schema, the description covers the compared attributes and input source, which is most of what an agent needs. It omits any note on how results are returned or ordered, a minor shortfall given the absent output schema.

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 carry meaning, and it does by stating the slugs come from search_apis and that 2-5 are needed. The count constraint partly restates the schema's minItems/maxItems, and the slug string format itself is never specified.

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 (APIs) plus the exact comparison dimensions (auth, free tier, HTTPS, pricing, docs summary) and the decision it supports ('to choose one'). It is clearly distinguishable from read-oriented siblings like get_api and search_apis.

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 search_apis as the source of the required slugs, which tells the agent the prerequisite step before calling. It does not state when-not to use it versus get_api or get_deal, so it stops short of full alternative routing.

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 only cover readOnlyHint=true, so the description carries the rest of the burden. It does disclose the response contents (docs, endpoints, auth, pricing, links) and its position in a workflow, which is valuable given there is no output schema; it does not mention payload size, rate limits, or error behavior when a slug is unknown.

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. The resource scope is front-loaded and the contents list plus the usage cue fit in a single compact block.

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 compensates by listing the returned payload categories, and the annotations cover the safety profile. It is nearly complete; only edge-case behavior (invalid slug, truncation) is 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?

Schema coverage is 0% – the single 'slug' property has no description at all – so the description must compensate. It does explain the parameter's origin ('from search_apis'), which the schema does not, though it says nothing about slug format or case sensitivity.

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 resource ('one API by slug') and enumerates exactly what it returns (documentation summary, endpoints, auth, pricing, links). The parenthetical '(from search_apis)' distinguishes it from the sibling that produces the plural list, so an agent can tell it apart from search_apis/compare_apis without opening any 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?

'Use before writing integration code' gives a clear situational trigger, and '(from search_apis)' implies the prerequisite that the slug must come from a prior search. No explicit when-not or named alternative, but the use context is unambiguous.

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 only declare readOnlyHint=true, so the safety profile is covered. The description adds real behavioral context beyond that: it discloses which fields appear conditionally (payment_url only at awaiting_payment, live_url only at live) and that recent messages are bundled into the response.

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?

One compact sentence with the most useful information (the status enumeration and conditional fields) up front. The parenthetical insertions are efficient, though the fragment style ('Also returns...') is slightly clipped rather than polished.

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 burden of describing returns; it covers status values, the conditional URLs, and messages, but omits the overall response shape and any error/not-found behavior. Combined with two fully undocumented parameters, it is adequate but leaves clear gaps.

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% and the description never mentions deal_id or deal_key. deal_id is self-evident from its name, but deal_key — plausibly a credential or scoping token — is left completely unexplained in both the schema and the description.

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 (a deal) and precisely what is returned — its status, conditional URLs, and last messages. It implicitly distinguishes itself from start_deal and send_message by being a read of existing deal state, though it never states an explicit verb like 'retrieve'.

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 when-to-use guidance, no prerequisite (e.g., that a deal must have been created via start_deal), and no reference to any alternative tool. The agent must infer the usage context entirely from 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?

readOnlyHint=true already tells the agent this is a safe read. The description adds that samples carry a verified flag, which is genuinely useful beyond the annotation, but says nothing about what happens when no sample exists for a language or whether the slug must refer to an existing API.

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 what the tool returns, followed by the usage trigger. No filler, though the trailing verified=true note is slightly tacked on rather than integrated.

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, so the description reasonably omits return-value detail, and the read-only annotation covers safety. However, the tool's sole required parameter (slug) is left semantically unexplained, which is a real gap for an agent trying to invoke it 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%, so the description must carry parameter meaning. It restates the language enum values (javascript, python, curl) that the schema already declares, and only hints that 'slug' identifies an API — it never explains the slug format, whether language is optional, or the default 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?

States a specific verb+resource: it returns ready-to-run example code for calling an API, in one of three languages. This is distinguishable from siblings like get_api (metadata) or search_apis (discovery), though no sibling is named 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?

"Use when you are about to integrate an API into code" gives a clear triggering context. It does not name alternatives (e.g., use get_api first to find the slug) or state exclusions, so it stops short of 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?

The readOnlyHint annotation already establishes that this is a safe read operation. The description adds context about the information returned (fixed prices, current sponsorship availability, rules), which helps set expectations but does not disclose behavioral traits like authentication requirements, rate limits, or side effects beyond the annotation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, well-structured sentence with no wasted words. It front-loads the core purpose and efficiently lists the key content categories, making it easy to scan.

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 simplicity of the tool (no parameters, no output schema, only a readOnlyHint), the description adequately conveys what the tool returns. It could be slightly more complete by specifying the return format or structure, but it covers the essential content.

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 no parameters, so there is no parameter schema to supplement. Per the rubric, zero parameters yield a baseline score of 4, and the description rightly does not spend words on parameters.

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's content: ways to get an API listed or sponsored, with prices, availability, and rules. It is specific enough for an agent to understand what the tool provides, though it uses a noun phrase rather than an explicit verb and does not differentiate from siblings.

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

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

No explicit when-to-use guidance or mention of alternatives is given. However, the description's content strongly implies the tool should be used when an agent needs information about listing or sponsoring an API on PublicAPIs.io, making usage inferable but not 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?

With only readOnlyHint=true available, the description carries real extra weight: it discloses the data source, the returned fields (name, description, category, link, signals), and the meaning of those signals (auth: none/api_key/oauth, free_tier, https). It does not mention pagination, result-count defaults, or rate limits, so it is strong 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?

Front-loaded with the core purpose, then return shape, then filters – a sensible order with no filler sentences. It is a single dense block rather than cleanly separated sections, which slightly hurts scannability for a 6-parameter tool.

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 read-only discovery tool with no output schema, the description covers purpose, the search corpus, the exact fields returned, and the filter vocabulary. An agent has everything needed to decide to call it and construct a valid query.

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 83%, so the schema already documents auth, free, https, query and category. The description restates the same filters with example syntax (auth="none", free=true, https=true), which is mildly useful but adds little beyond the schema, and the 'limit' parameter is undocumented in both places.

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+resource ('Find a public API or data source') and names the backing corpus (1,500+ APIs on PublicAPIs.io). It clearly implies a search/discovery role that separates it from get_api and compare_apis, but never names a sibling explicitly, so differentiation is inferred rather than stated.

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 trigger ('use this whenever the user (or your code) needs an API, dataset or third-party service') with concrete domain examples (weather, geocoding, payments, crypto prices). It offers no when-not guidance or explicit routing to get_api/compare_apis, so it stops short of 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?

With no annotations, the description carries the full behavioral burden. It usefully discloses that the call returns the broker's answer and the deal status (valuable given no output schema), but says nothing about permissions, synchronous vs asynchronous delivery, rate limits, or what happens on a closed deal.

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 the action front-loaded and the return behavior second; nothing is wasted. It is arguably too terse given the unexplained parameters, but structurally it is clean.

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 3-required-parameter mutating tool with no annotations, no output schema, and 0% schema description coverage, the description covers only purpose and a hint at the return value. It leaves parameter meaning and preconditions undocumented, which is not enough for reliable 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?

Schema description coverage is 0% for all three required parameters. "Reply to the broker" loosely implies the message parameter, but deal_id and especially deal_key (likely a credential) are entirely unexplained in both schema and description, so the description fails to compensate for the coverage 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?

States a specific verb and resource (reply to the broker) plus the scope constraint (an open deal), which separates it from read-oriented siblings like get_deal and start_deal. It does not explicitly name or contrast any sibling, but the purpose is unambiguous.

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?

"In an open deal" implies the precondition that the deal must already exist and be open, which is useful routing context versus start_deal. However, there is no explicit when-to-use/when-not guidance and no mention of what to do if the deal is not open or already closed.

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 return values (deal_id, deal_key), that both must be kept to continue, and that a human approves every deal before payment. It omits auth requirements and any rate/turnaround expectations, so it is strong but not complete.

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, each earning its place: purpose first, how to call it second, what comes back and the approval constraint third. No filler or repetition.

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

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

There is no output schema, so the description properly explains the return payload and the deal continuation keys, plus the human-approval workflow. Combined with the low schema coverage, this is nearly complete for a 6-parameter tool, with only the two obvious optional contact fields left implicit.

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 only 17%, so the description must compensate, and it does for the important fields: message (plain language), api_name, website and contact_email. The remaining two parameters (company, contact_name) are optional and self-explanatory from their names, so the gap is minor.

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: 'Open a conversation with the PublicAPIs.io broker agent to list or sponsor an API.' That is enough to tell it apart from read-oriented siblings like get_deal and search_apis, but it never names a sibling explicitly, so it falls short of the top tier.

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 clear invocation guidance ('Say what you want in plain language and include the API name, website and a contact email if you have them'), which tells the agent how to populate the call. It stops short of stating when NOT to use it or naming send_message as the continuation alternative.

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