AgentoolRank

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

With no annotations, the description carries the full burden, and it does disclose the return payload ('source tool slug and its recorded alternatives with GitHub stats'). However it says nothing about read-only nature, auth/permission requirements, rate limits, or result completeness, leaving meaningful behavioral 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, front-loaded with the when-to-use condition, then the parameter contract, then the return shape. No filler or restatement of the tool name.

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, the description covers when to use it, how to form the argument, and roughly what comes back. It is nearly complete; only auth/read-only expectations are unstated, which is minor given the clearly read-oriented name.

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

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

Schema description coverage is 0%, so the description must compensate, and it does: it defines slug as 'the tool identifier returned by search_tools (for example, dify)' and explicitly warns against URLs or directory domains. This is exactly the disambiguation a single undocumented parameter needs, though it could note case/format constraints.

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 ('alternatives to a known AI agent tool') and explicitly scopes out a competing interpretation ('not launch directories'). This distinguishes it from sibling tools like search_tools and get_tool, which an agent could otherwise confuse it with.

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 you need alternatives to a known AI agent tool, not launch directories' gives a clear triggering condition plus a negative exclusion. It does not name the specific sibling tool an agent should reach for when launch directories are wanted, so it stops short of explicit 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?

With no annotations, the description carries the disclosure burden and does well: it states the required credentials, and that it returns review status, queue position, and a listing URL when available. It does not cover failure modes (invalid/expired token) or timing expectations, so it falls short of a full 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 sentences, front-loaded with the use condition, then prerequisites, then the exclusion. Every clause carries information; 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 two-parameter read tool with no output schema, the description covers prerequisites, return content, and the sibling boundary. Minor gaps remain around error/expiry behavior, but an agent has enough to call 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 coverage is 0%, so the description must compensate; it identifies both parameters and, crucially, their provenance ('from that submission'), which the schema does not convey. It stops short of describing the token's format or validity window.

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 verb+resource (checking AgentoolRank review status of a submitted tool), ties it directly to submit_tool as the producing action, and explicitly distinguishes itself from my_progress. An agent can identify the tool's role without opening the 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 states exactly when to use it (after submitting via submit_tool), what it requires (submission_id and status_token from that submission), and names the alternative for a related but different need (launch-directory progress via my_progress). Nothing is left 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?

No annotations are provided, so the description carries the full behavioral burden. 'Get details' implies a read-only lookup and the enumeration of returned fields describes the payload, but there is no disclosure of auth requirements, rate limits, or failure behavior (e.g., unknown slug) for a tool that takes an externally sourced identifier.

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 front-loaded sentence with a bracketed category tag, then the essential payload list — nothing redundant. It is appropriately sized for a single-parameter lookup, though the tag prefix is mild structural noise.

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 read-only lookup with no annotations and no output schema, the description compensates by enumerating the returned fields, which is what the agent would otherwise lack. It leaves only minor gaps around error behavior and the slug format.

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% for the single 'slug' parameter, and the description only adds its provenance ('from search_tools'). It does not state the expected slug format or that the value must come from a prior search result — useful, but partial compensation for a fully undocumented 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 and resource ('Get details for one tool by slug') and enumerates exactly what is returned (GitHub stats, capabilities, best-for, limitations, alternatives). It also distinguishes itself from search_tools by naming it as the source of the slug, so an agent can tell the lookup apart from the sibling search 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 parenthetical '(from search_tools)' implies the usage pattern: call search_tools first, then drill into one result. However, it never says when NOT to use this tool, nor does it route to the close sibling get_alternatives even though 'alternatives' is listed as returned data — an overlap the agent must resolve by 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?

With no annotations, the description carries the full burden and does well: it discloses the auth requirement (Submit Kit key), the status semantics of outstanding sites ('issued'), and a non-obvious caveat that remaining allowance is computed as cap minus issued rather than a returned field or guaranteed value. It does not explicitly state read-only safety, but for a retrieval tool the disclosed caveats are the higher-value information.

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 definition is front-loaded with the usage directive, then returns, then caveats, then the sibling exclusion — a sensible order that keeps dense information scannable. It is a single long run-on with several clauses, slightly heavier than ideal, but every sentence adds distinct value.

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 and no annotations, the description fully enumerates the return fields, explains the derived 'remaining allowance' value, clarifies the status mapping for outstanding sites, and rules out the neighboring tool. An agent has everything needed to call it correctly and interpret the response.

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

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

Schema coverage is 0% for the single 'key' parameter, so the description must compensate, and it does: 'requires the Submit Kit key' tells the agent what credential to supply. It does not describe format or error behavior for an invalid key, keeping it out of the top band.

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 the resource clearly (submission/progress data) and enumerates exactly what is returned (product_type, cap, sites, progress_page, and the count categories), which lets an agent identify it as a progress-retrieval tool. It also distinguishes itself from the sibling get_submission_status. It stops short of a single crisp verb+resource sentence, front-loading usage guidance instead, so a 5 is not quite earned.

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 triggers ('Use this after report_result or to resume a session') and an explicit exclusion with the correct alternative named ('Not for AgentoolRank listing review status — that is get_submission_status'). Nothing about when to select this versus siblings is left 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?

With no annotations, the description carries the full behavioral burden and does so well: it discloses the return cardinality (exactly one, or possibly report_first/done), the quota constraints (at most 3 unreported sites, up to 50 per key), and the stateful binding of product_type on first issuance. These are non-obvious traits an agent could not infer from the schema alone.

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 identification header, then workflow, then constraints, then the alternative. Dense and multi-clause, but nearly every clause carries distinct information; only slight compression could tighten it.

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 must explain returns, and it does (one directory, report_first, or done) plus quotas and state binding. It stops short of explaining what report_first requires from the agent, leaving a small gap, but the tool is usable as documented.

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, but the description adds real meaning: the key is a 'Submit Kit key' (context) and product_type 'is bound on first issuance' (stateful, one-shot semantics beyond the schema's 'first call only').

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 the resource (launch directories) and states precisely what comes back: 'Returns exactly one next directory when available.' The verb is implicit (an iterator-style fetch) rather than explicit, but an agent can distinguish it from siblings like recommend_directories and get_submission_status.

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 the triggering condition ('when working through launch directories with a required Submit Kit key'), the follow-up workflow ('submit there, then call report_result'), and an explicit alternative for a different need ('For a free overview list, use recommend_directories'). This is textbook when-to-use/when-not 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?

With no annotations, the description carries the full burden and does well: it discloses the free tier (top 5, no key required), what is returned (conditions and submission steps; full overview plus directories to avoid with a key), and the pricing gate ($29). It omits error handling for an invalid key and any rate/limit behavior, so it falls 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?

Three tight sentences, front-loaded with the free-tier behavior before the paid alternative. The bracketed '[Launch directories]' prefix is mildly redundant filler against the tool name, keeping it from a 5.

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 must describe returns, and it does (top 5 with conditions and submission steps; full list and directories to avoid with a key). It leaves response format and failure modes unaddressed, which keeps it short of complete.

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

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

Schema coverage is 75%, so baseline is 3, and the description adds real meaning for 'key' beyond the schema (the $29 cost and that it also unlocks 'directories to avoid'). It adds nothing for languages/open_source, which the schema already documents.

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... best-fit launch directories'), names the scope ('for a product_type: top 5'), and explicitly distinguishes itself from the sibling next_directory. An agent can pick it without opening either 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 when-to-use ('when you need a free overview') and names the alternative path with the condition that selects it ('to work through the full list one directory at a time with a Submit Kit key, use next_directory instead'). No inference required.

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 mostly delivers: it discloses the state mutation ('clears that site's unreported slot'), the auth-style requirement (same Submit Kit key), and the non-obvious deferred semantics that 'listed' only counts after a daily live check. It stops short of stating error behavior, idempotency, or whether a domain can be re-reported.

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 the routing constraint before the mechanical details, and every sentence carries information. The bracketed '[Launch directories]' tag adds little, and the final 'only a lead' sentence, though useful, could be tightened.

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 must convey the aftermath; it does so by saying the outcome is recorded and the unreported slot cleared, plus the caveat on 'listed'. Remaining gaps are the response shape on failure and re-reporting rules, which are minor for a simple five-param write.

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 40%, but the description compensates: it enumerates the required fields (key, domain, status), lists the full status enum, marks listing_url and note as optional, and adds meaning to 'key' by tying it to the Submit Kit. Only the note's 300-char limit is left to 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 (records/reports an outcome) on a specific resource (a domain issued by next_directory), and explicitly names what it is NOT (submitting a tool to AgentoolRank). An agent can separate this from submit_tool and next_directory without opening either 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 trigger ('when recording an outcome for a domain issued by next_directory') plus an explicit exclusion ('not submitting a tool to AgentoolRank'), and names the prerequisite key. The conditions that select this tool versus its siblings are stated outright.

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 burden. It does disclose the ranking signal (GitHub activity) and the return contents (stars, 30-day growth, capabilities, alternatives), but says nothing about auth, rate limits, or result ordering beyond the ranking mention.

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 with the search scope front-loaded and no filler. Slightly overloaded by the parenthetical category list, but every clause is informative.

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

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

For a simple two-parameter search with no output schema, the description covers scope, ranking, and return fields adequately. It omits routing guidance against siblings, which is the main remaining gap.

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 both parameters are already documented with a format example and range. The description adds no syntax or query-semantics detail beyond the schema, making the baseline 3 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 resource (open-source AI agent tools), enumerating the covered categories so the agent knows the directory's scope. It does not explicitly differentiate from siblings like get_tool or get_alternatives, so it falls 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?

No when-to-use guidance and no named alternatives, despite get_tool and get_alternatives being obvious siblings. The only hint of usage is the schema's query example, which the description does not reinforce.

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 and does well: it discloses that the free listing is queued (not immediate), that the response surfaces paid upsell options with a checkout_url intended for the human to pay, and that it returns submission_id + status_token plus a message_for_human summary. It omits auth requirements, idempotency, and failure modes, so 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?

Three sentences, front-loaded with the bracketed directory tag and the core action, followed by the response contract. The category parenthetical is long but informative rather than filler; overall no sentence is wasted.

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 must explain returns, and it does: submission_id, status_token, the paid option list, and message_for_human. Combined with covered behavior for an 8-parameter mutation tool, it is nearly complete, missing only error/auth edge cases.

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 already 88%, so the baseline is 3, but the description adds real meaning: it explains that max_budget_usd and deadline_days drive the paid-option recommendation logic and that email is only used for go-live notification. That is behavioral context the schema's one-liners do not supply.

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: listing an AI agent tool on AgentoolRank, and enumerates the categories accepted in the parenthetical. It is clearly distinguishable from siblings like get_tool, search_tools, and get_submission_status, which are read/lookup 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 establishes the full workflow context: free listings are queued, paid options are returned with price/days/checkout_url, and the cheapest fitting option is recommended against max_budget_usd/deadline_days. It also routes the agent forward to get_submission_status. It does not explicitly state when NOT to use it or prerequisites (e.g., required email/url), 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.