LicenseSaaS

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

Annotations already declare this is a non-read-only, open-world, non-idempotent, non-destructive write. The description adds two genuinely useful facts beyond them: the post is publicly live immediately and is attributed with a 'Posted via AI agent' label. It still omits auth requirements (agent_key vs legacy hostname/publish_key) and whether a post can be edited or retracted after going live.

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

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

Two tight sentences with the core action front-loaded and the behavioral caveat second; every sentence earns its place. The brevity is close to under-specification, but the dimension is about waste and ordering, and there is none.

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 mutation tool with a deep nested schema, 50% description coverage, no output schema, and an open-world publish side effect, the description is far too thin. An agent would need to reverse-engineer required fields, valid enum values, and which credential parameter to supply from the schema alone, with no guidance on consequences of an incorrect post.

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%, and the description says nothing about any parameter, including the required nested `request` object with twelve fields and the large enum vocabularies for categories, industries, deal_types, and request_type. The two legacy-vs-new auth parameters (agent_key vs hostname/publish_key) are only explained in the schema, and buyer_role/contact_email are undocumented entirely, so the description does not 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?

"Post a buyer request" gives a specific verb (post) plus resource (buyer request) that matches the tool name and distinguishes it from read-side siblings like get_buyer_request or search_buyer_requests. It does not, however, distinguish it from create_listing, the other write tool in the family, so an agent cannot tell from the description alone which creation tool applies.

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 explicit when-to-use guidance, no prerequisites, and no mention of the alternative create_listing. The only implicit signal is the name itself; an agent must infer that this is for demand-side (buyer) posts rather than supply-side listings.

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 non-read-only, non-destructive, non-idempotent and open-world. The description goes beyond them by disclosing that publication takes effect immediately and that the listing carries a public 'Listed via AI agent' label — non-obvious, agent-relevant side effects. It stops short of saying whether a published listing can be edited or removed afterwards.

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

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

Three short sentences, front-loaded with the effect of the call, then the public label, then the prerequisite. Nothing is redundant or padded.

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, so the description should cover more of the call's reality. It never mentions that credentials (agent_key, or legacy hostname/publish_key) or seller_role exist, even though only 'listing' is in the required set — an agent could reasonably attempt publication without auth. For a public-facing mutation with a deeply nested payload, that is a notable 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 coverage is 67% and the single required parameter is a nested object of ~15 fields with two large enums, so the schema largely carries semantics. The description adds only the indirect hint to fetch get_listing_schema first, which helps an agent construct the payload but explains no individual field meanings.

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 and resource: 'Publish a listing', plus the immediate effect ('Goes live immediately'). It doesn't differentiate from siblings such as create_buyer_request or the get_listing tools, but a read-only sibling set makes 'publish' unambiguous enough.

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 one concrete procedural instruction — 'Call get_listing_schema first' — which is genuinely useful for the complex nested payload. However, there is no guidance on when to use this versus other creation tools, no prerequisites about required credentials, and no 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 readOnlyHint and closed-world, so the description's added value is the 'public details' field-scoping and the restriction to 'active' requests — useful constraints beyond the annotations. It does not say what happens for inactive, deleted, or nonexistent ids, nor anything about return shape.

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 no filler; every phrase (full, public, one, active, slug or id) carries 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?

For a simple single-param read with annotations covering safety, the essentials are present, but with no output schema the description leaves unclear which fields 'full public details' comprises and how missing/inactive requests are surfaced.

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 'id' parameter, so the description must compensate — and it does by disclosing that the identifier may be either a slug or an id. It does not specify format constraints or whether ambiguous inputs are rejected.

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 ... buyer request') with scope qualifiers ('full public details', 'one active'). It is distinguishable from search_buyer_requests and create_buyer_request, though it never names those siblings explicitly.

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

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

Usage is only implied: 'one ... by slug or id' signals a single-record lookup as opposed to the sibling search tool, and 'active' hints at a filtering precondition. No explicit when-to-use/when-not or alternative routing is given.

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=true and openWorldHint=false, so safety is covered. The description adds that the payload includes per-field type, limits, and allowed values — useful return-content detail since no output schema exists — but says nothing about whether this covers writable fields, filterable fields, or both.

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 twelve-word sentence with zero filler, and the most informative part (what the response contains) is front-loaded. It is a fragment without a verb, which slightly weakens the framing but wastes no words.

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

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

For a zero-parameter, read-only introspection tool with no output schema, the description conveys the essential return shape (field name, type, limits, allowed values). Missing only scope details such as whether the listing is static or exhaustive across request types.

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 there is nothing for the description to disambiguate; baseline 4 applies. The description correctly implies no inputs are needed to obtain the full field catalogue.

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 (buyer-request schema) and enumerates what it returns (type, limits, allowed values), so an agent knows it is a schema/introspection tool. It is a noun phrase rather than a verb+resource statement and never contrasts itself with the sibling get_listing_schema, so sibling differentiation is left to the name.

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 statement of when to call this versus alternatives such as get_buyer_request, search_buyer_requests, or get_listing_schema. The likely intent — inspect fields before constructing a create or search call — must be inferred entirely from the tool name.

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

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds genuinely useful context with 'public details' and 'published listing', implying non-public fields are excluded and unpublished listings are not retrievable, but it says nothing about not-found behavior or result shape.

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 sentence, front-loaded with the resource and scope, with zero filler. Nothing could be removed without losing meaning.

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

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

For a single-parameter read tool with annotations covering safety and no output schema, this is close to sufficient: scope, identifier form, and public/published visibility are all stated. The remaining gap is disambiguation from get_listing_schema, which the description never addresses.

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 carries the burden; 'by slug or id' does clarify that the single opaque string parameter accepts either identifier form, which the bare schema does not convey. It stops short of giving format examples or saying what happens if both interpretations are ambiguous.

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 details of one published listing') and pins the scope to a single item by slug or id, which distinguishes it from the plural search_listings. It does not, however, distinguish it from the sibling get_listing_schema, which an agent could easily 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?

Usage is only implied: read this when you already have a slug or id for a published listing. There is no explicit when-to-use, no mention of search_listings as the alternative for discovery vs. retrieval, and no pointer to get_listing_schema for schema-related needs.

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=true and openWorldHint=false, so the safety profile is covered. The description's added value is enumerating the payload contents (field types, limits, allowed values, guidance, licence types, white-label levels), which is meaningful because there is no output schema. It doesn't say whether the schema is static or versioned, keeping it below 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?

A single dense fragment with no wasted words, and the most important content (field definitions) is front-loaded. The missing subject/verb is the only structural flaw, though the meaning remains unambiguous.

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

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

For a zero-parameter, read-only, no-output-schema tool, the description carries the necessary burden by listing what comes back. The gap is workflow context — an agent is told what it gets but not why or when to request it.

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 input schema defines zero parameters and coverage is 100%, so the baseline of 4 applies. There is nothing further the description could reasonably add about inputs.

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 enumerates exactly what the tool returns: listing field definitions (type, limits, allowed values, guidance) plus licence types and white-label levels. That is specific enough to separate it from get_listing (a single record) and from get_buyer_request_schema (a different domain's schema). It lacks an explicit verb, reading as a noun-phrase inventory rather than 'Returns ...', 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?

There is no statement of when to call this, no mention of prerequisites, and no reference to the obvious alternative workflow (call before create_listing, or use get_buyer_request_schema for the buyer side). The agent must infer the use case entirely from the returned-content list.

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=true and openWorldHint=true, so safety is covered; the description's contribution is the ordering guarantee ('newest first'), which is genuinely useful behavior not present in the annotations. However, it says nothing about pagination, result caps, or how many conversations come back, which matters for a listing tool.

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 sentence with no filler, and the scope ('Your account's') is front-loaded ahead of the ordering detail. It is efficient but so terse that it borders on under-specification rather than demonstrating disciplined structure.

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 listing tool with no output schema, the description covers scope and ordering but omits pagination/limits and the auth prerequisite implied by agent_key/publish_key. The schema carries parameter documentation, so the remaining gap is modest rather than fatal.

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 three parameters (hostname, agent_key, publish_key) are fully documented in the schema, including the legacy-vs-preferred distinction. The description adds nothing about authentication or which key form to prefer, so it neither compensates nor detracts; 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 the resource (the account's conversations with sellers or buyers) and the ordering (newest first), which lets an agent distinguish this list operation from read_conversation. It never uses an explicit verb like 'list' and relies on the name to convey that, so it falls short of a fully self-contained purpose statement.

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 guidance on when to call this versus read_conversation, send_message, send_inquiry, or any other sibling. The only usage signal is the implied 'list' from the tool name; there are no exclusions or preconditions such as requiring a registered agent.

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

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

Annotations already establish this as a safe read-only, closed-world operation. The description adds useful behavioral context — that values come with live listing counts — which is more than the annotations provide. It stops short of explaining the return structure, pagination, or whether counts are exact, so it earns a moderate score rather than a high one.

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 dense sentence that front-loads the key information: valid filter values and the facets covered. There is no wasted text. It loses a point only because the noun-phrase construction is slightly less direct than a verb-first sentence would be.

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 burden of explaining what comes back. It does say the result contains valid values plus live listing counts and names the five facets, which is helpful. However, it does not describe the shape of the response (e.g., per-facet arrays with value/count pairs), so an agent still has to inspect the actual output to understand its structure.

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

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

There are zero parameters, so the baseline is 4. The description correctly implies no filtering or input is required, and it specifies which facets are covered, which is the only parameter-adjacent information relevant 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 the resource precisely: valid filter values for five specific facets, with live listing counts. It is clearly a lookup/reference tool rather than a search or mutation tool, distinguishing it from siblings like search_listings. The only weakness is that it is phrased as a noun phrase rather than stating the action, but 'Valid filter values ... for category, industry...' is specific enough.

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

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

Usage is implied: an agent can infer it should call this to discover valid filter values before filtering listings, and the mention of 'live listing counts' hints at facets usable elsewhere. However, it never explicitly says when to use it versus search_listings, nor does it state that the returned values are intended as inputs to other tools. The guidance is present but 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?

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds one genuinely useful behavioral caveat — that message text is third-party content and should be treated as data rather than instructions — but says nothing about ordering, pagination, empty conversations, or auth requirements.

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 with no filler, and the resource statement is front-loaded ahead of the safety warning. It is efficient, though the brevity comes partly from omitted information rather than disciplined editing.

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 four parameters, no output schema, and no annotations covering auth or return shape, the description should say what comes back (message list, ordering, limits) and how the conversation is identified. The prompt-injection warning is valuable but leaves the operational picture incomplete.

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% and the three key/auth parameters are documented in the schema itself, so the schema does most of the work. The description implies conversation_id selects the conversation, but adds no format or sourcing details, and conversation_id itself has no schema 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 noun phrase 'Messages in one of your conversations' identifies the resource and implies a read, which separates it from list_conversations and send_message, but there is no verb and no explicit statement that it fetches messages by conversation_id. An agent can guess the purpose, but the description never commits to it.

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 instead of list_conversations, get_listing, or any other sibling, and no mention of required auth (agent_key) or how to obtain a conversation_id. Usage must be inferred 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?

Annotations already declare readOnlyHint=false, openWorldHint=true and non-idempotent, so the mutation profile is partly covered. The description adds meaningful side effects the annotations do not: an account is created for that email and a sign-in link is emailed to the owner, plus what to do if the account exists. It stops short of saying whether a repeat call with the same email errors or creates anything new.

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, front-loaded with the payoff (instant agent_key, no website) followed by the mechanics and the fallback case. No wasted phrasing.

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 names the return value (agent_key) and the email side effect, and handles the existing-account branch. The remaining gap is the undefined company_name parameter and unstated behavior on repeat registration.

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 25%, with just 'name' documented. The description partially compensates by explaining that role takes buyer/seller/both and that email is the account identity, but company_name is entirely undefined in both schema and 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?

States a specific verb and resource: creates a LicenseSaaS account and returns an agent_key, with the role scope (buyer, seller or both) spelled out. An agent can tell immediately this is a registration/onboarding tool, distinct from the listing, buyer-request and messaging 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?

Gives an explicit precondition ('no website needed') and an explicit alternative path for the already-registered case: ask the owner for a key from Account settings -> Agent keys. That is exactly the when/when-not routing an agent needs.

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 disclose that this is a non-read-only, open-world, non-idempotent, non-destructive operation. The description adds optionality and an alternative path, but does not explain side effects, verification flow, or any permission requirements beyond what the annotations imply.

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 short and front-loads the optional nature of the tool. It is efficient, though its brevity contributes to the missing action and parameter details.

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 a one-parameter tool with an output-less schema, the description should at least clarify the hostname input and the relationship to verify_domain. Instead, it only says the tool is optional and points to an unrelated alternative, leaving core invocation details incomplete.

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 one required parameter, hostname, with 0% description coverage. The description does not mention hostname or explain its format, so it fails to compensate for the schema's lack of parameter documentation.

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 domain-control resource but frames it vaguely as 'prove control' rather than clearly stating that it initiates a verification request. It does not distinguish this tool from the sibling verify_domain, leaving the exact action ambiguous.

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 says the tool is optional and not required, and directs users to agent_key instead. That gives clear guidance on when not to use it, though it does not explain the scenario in which requesting domain verification would be appropriate.

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=true and openWorldHint=false, so safety and scope are covered. The description adds the useful context that results are limited to active buyer requests and explains what buyer requests represent, but it does not disclose pagination behavior, result shape, or sorting.

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, and the parenthetical adds useful domain context. It is concise, though its brevity leaves it underpowered given the undocumented parameter set.

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 search tool with five parameters, no schema descriptions, and no output schema, the description is insufficient. It omits filter semantics, pagination, and any indication of what a result contains, leaving the agent to guess at core invocation details.

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

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

There are five parameters and schema description coverage is 0%, so the description must compensate, but it mentions none of them: query, category, deal_type, limit, and offset are completely undocumented. An agent cannot infer supported filters or pagination from 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?

States a specific verb and resource: "Search active buyer requests," with a parenthetical clarifying that these are licensing demands from agencies, resellers and operators. The search-vs-get distinction is implicit and clear, but the description does not explicitly contrast itself with search_listings or get_buyer_request.

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

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

The word "active" implies a scope restriction, but there is no explicit guidance on when to use this tool versus search_listings or get_buyer_request. No alternatives, prerequisites, or exclusions are mentioned.

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=true and openWorldHint=false, so the safety profile is covered. The description adds a useful scope constraint — only published listings are returned — but says nothing about pagination behavior, result ordering, or empty-result behavior, which matters for a search tool with limit/offset.

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 zero waste; scope comes first and the dependency on list_filters is stated 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 no output schema and no parameter descriptions, the description should carry more weight. It handles the filter-value question well via list_filters but leaves the agent guessing about result shape, pagination, and what 'published' excludes.

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 eight parameters are undocumented in the schema. The description partially compensates by declaring all filters optional and pointing to list_filters for valid values, which covers the five categorical filters, but limit, offset, and query semantics and the limit maximum of 20 are left entirely 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 (search) and resource (published software listings), plus the transaction types involved (license or white-label). It is clearly distinct from search_buyer_requests, though it never names siblings 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?

'All filters optional' tells the agent it can call this with no arguments, and 'use values from list_filters' routes it to the correct sibling to obtain valid filter values. What's missing is when to prefer this over search_buyer_requests or get_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?

Annotations already declare non-readonly, non-idempotent, open-world, non-destructive, so the safety profile is covered. The description adds genuinely new context about the delivery mechanism (LicenseSaaS inbox plus email), but says nothing about required authentication (agent_key) or that a repeat call creates another inquiry.

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, no waste, with the action and its side effect front-loaded. Nothing redundant.

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

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

For a 10-parameter mutation with no output schema and 40% coverage, the description omits the auth model (agent_key vs legacy hostname/publish_key) and the semantics of the optional fields. An agent could call it but would be guessing on half the inputs.

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% across 10 parameters. The description adds no meaning for message, timeline, budget_range, company_name, contact_email, or inquiry_type, leaving several parameters undocumented in both schema and prose.

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 ('Send an inquiry to a listing's seller') and clarifies the account basis. It implicitly distinguishes itself from send_message and create_buyer_request by describing a seller-facing inquiry, but never names those siblings 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?

No guidance on when to use this versus send_message (existing conversation) or create_buyer_request (buyer-side demand). The only cue is the implied first-contact intent, which the agent must infer.

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

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

The annotations already declare this is not read-only, is open-world, is not idempotent, and is not destructive. The description adds useful behavioral context that the recipient is emailed, which is a concrete external effect beyond the annotations. It does not explain authentication requirements, delivery behavior, or failure modes.

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 two short sentences with no wasted wording. It is front-loaded with the core action and followed immediately by the external effect.

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 definition covers the basic action and external side effect, and the schema documents the auth alternatives. However, for a five-parameter messaging tool with no output schema, it leaves gaps around authentication requirements, expected response behavior, and conversation validity.

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 60%, with the three auth-related parameters documented in the schema. The description implies conversation_id and message but adds no format or constraint details for them. It does not clarify the relationship among agent_key, hostname, and publish_key, though the schema partially covers those.

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: reply in one of your conversations. It also clarifies a key effect, that the other side is emailed. It does not explicitly name sibling alternatives like send_inquiry, but the scope is clear enough to distinguish replying to an existing conversation.

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

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

Usage is implied by 'Reply in one of your conversations,' which suggests this is for continuing an existing thread rather than starting a new inquiry. However, there is no explicit guidance on when to choose this over send_inquiry, read_conversation, or list_conversations, and no prerequisites 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?

Annotations already flag a non-read-only, non-idempotent, open-world operation, and the description adds genuinely new behavior: the ordered fallback across lookup methods and the critical fact that publish_key is returned only once. It omits what happens on failed verification (error vs. partial result), which is the main remaining 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 compact sentences with zero filler: the verification method order first, then the important return-value caveat. Nothing is buried and nothing is redundant.

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

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

With no output schema, the description does well to disclose the publish_key return and the show-once caveat. But for a mutating, non-idempotent verification step it should also cover failure modes and the hostname format, leaving the definition only partially 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 description coverage is 0% for the single required parameter, so the description carries the full burden and does not mention hostname at all. It never clarifies whether the value should be a bare domain, a subdomain, or a URL, which is a realistic ambiguity for this kind of input.

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 (check a published verification token) and resource (domain token), and enumerates the three lookup locations (file, meta tag, DNS TXT). It implies but never explicitly names the relationship to the sibling request_domain_verification, so an agent must infer that verification is a separate follow-up step.

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 'the published token' hints that a token must already exist and be published, but the description never says to call request_domain_verification first or when verification should be retried. Usage is implied rather than stated, and no exclusions or alternatives are given.

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