whatsapp-wyjbao

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

No annotations are provided, so the description carries the full burden. It does disclose two genuinely behavioral facts beyond the schema: that looking does not follow the channel (no side effect) and that billing is 1 credit per call. It omits auth requirements, behavior on invalid/expired codes, and rate limits, which a no-annotation read tool should ideally cover.

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?

Compact and mostly front-loaded: resource and inputs come first, followed by the side-effect note, group tag, and cost. The opening is a sentence fragment rather than a verb-led statement, a minor structural blemish, but nothing 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?

With no output schema, the description usefully enumerates what is returned (name, description, follower count via channelMetadata.size, verification, creation time, settings), which is real compensating value for a simple single-parameter read tool. Missing error/edge-case behavior and auth context keep it from a 5.

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?

Only one parameter, and the schema documents it at 100% coverage with an example URL. The description's phrase 'invite link or code' restates the schema's own description without adding syntax or formatting detail, so baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names the specific resource (a WhatsApp channel) and the lookup key (invite link or code), and enumerates the returned fields, so an agent knows exactly what this retrieves. It does not explicitly contrast itself with siblings like get_v1_channel_messages or get_v1_channels_search, so differentiation is only implicit through the field list.

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: call this when you have a channel link or code and want its metadata. However, there is no explicit 'use X instead when Y' routing against channels_search (which presumably finds channels without a known code) or channel_messages, so the agent must infer selection.

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 a fair job: it discloses the non-mutating side-effect boundary ('Does not follow the channel'), the ordering of results, and a concrete billing cost of 2 credits per call. It stops short of stating auth requirements, rate limits, or pagination behavior beyond the limit parameter.

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 with the purpose front-loaded, followed by the side-effect disclaimer and cost metadata. 'Group: Channels' is close to filler, but the billing note earns its place for an agent weighing cost.

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 and no annotations, so the description must cover return shape and side effects — and it does, listing the fields returned and clarifying that no follow occurs. Only auth/permission expectations and explicit result-volume behavior are left 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 100% and both parameters are documented in-schema, including the code format/example and the 1–100 limit range with default. The description adds only the ordering semantics ('newest last'), which the schema does not state, so baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb and resource (latest posts of a WhatsApp channel) and even specifies the return shape — text, type, time, links, media presence — plus ordering ('newest last'). It is clearly distinct from get_v1_channel (channel metadata) and the search/invite/check siblings, though it never explicitly names an alternative to contrast against.

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 context is implied by 'latest posts' and the negative clause 'Does not follow the channel', which tells the agent this is a read that will not subscribe it. However, there is no explicit when-to-use vs. when-not guidance and no named alternative for related needs (e.g., channel profile via get_v1_channel).

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 burden and does disclose real behavior: the exclusion of followed channels, the billing rate (1 credit per call), and the fields returned per channel. It omits pagination/rate-limit behavior, but the safety and cost profile is otherwise covered by the description itself.

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 dense paragraph, front-loaded with the core search behavior, followed by output fields, exclusions and billing. Every sentence carries information; nothing is padding.

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

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

With no output schema and no annotations, the description goes out of its way to enumerate the returned fields (followers, verification, description, invite code) and the billing cost, which is exactly what is missing from structured data. Minor gaps remain around pagination and result ordering.

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 the schema already documents view, limit, query and country. The description reinforces the query-vs-view relationship ('without a query the directory's recommended...') but adds no format or range detail beyond the schema, so the baseline of 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?

It names a specific verb and resource ('channel directory: channels whose name matches query...') and spells out the two operating modes (query-driven vs. view-driven). It also distinguishes itself from siblings by explaining that the returned invite code is meant to be used with Get Channel / Get Channel Posts.

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 clearly states the query/no-query branches and notes that followed channels are excluded, which tells the agent when results will be incomplete. It points at the follow-up siblings to use with the invite code, but does not explicitly say when to prefer this over a direct channel lookup.

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 discloses several behavioral traits: it is a read-only operation ('Looking does not join'), it specifies error behavior for bad invite codes (404 `not_found`), and it states billing ('1 Credits' per call). It does not mention authentication requirements or rate limits, but the core side-effect and error semantics are well covered.

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 front-loaded with what data is returned, then adds usage, error, and billing notes. It is a single dense sentence for the return fields, but every detail is useful because there is no output schema to document the returned 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?

Given that the tool has no output schema, the description fully compensates by enumerating the returned fields (group name, description, size, creation time, settings, owner, participants). It also covers the non-joining behavior, error response for invalid codes, and billing, leaving no meaningful gap for an agent 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 description coverage is 100%, so the `code` parameter is fully documented in the schema itself. The description adds no additional syntax or format details beyond what the schema already provides, making the baseline score of 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?

The description states a specific resource and operation: it returns what WhatsApp shows anyone who opens a group's invite link — group name, description, size, creation time, settings, owner, and participants. It is clearly distinguishable from siblings like get_v1_channel or get_v1_number_profile because it targets group invite links specifically.

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 context — 'Looking does not join the group' — which tells the agent this is a non-joining preview operation. It does not explicitly name alternatives or when-not-to-use conditions, but the sibling tools are unrelated enough that no exclusion is needed.

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 `registered: false` is normal, not an error, and states the billing cost of 1 credit per call. It does not cover auth requirements, rate limits, or the full response shape, so it remains only minimally sufficient.

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, front-loaded, and wastes no words. The core purpose comes first, followed by a critical interpretation note, group label, and billing detail. Each sentence contributes useful context.

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 check with no output schema and no annotations, the description gives an adequate picture: what is checked, what the result means, and the billing cost. It could more fully specify the response format or any auth/rate-limit constraints, but the essential invocation context is present.

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

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

Schema description coverage is 100%, and the single `phone` parameter already has a detailed format description. The tool description adds no additional parameter semantics beyond what the schema provides, so the baseline of 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?

The description states a specific verb-resource pair: checking whether a phone number has a WhatsApp account and retrieving its WhatsApp id. It is clear and concrete. However, it does not explicitly differentiate the tool from its sibling get_v1_number_profile, leaving the agent to infer the distinction.

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 the purpose, and the note that an unregistered number is a normal answer rather than an error is helpful interpretation guidance. Still, there is no explicit when-to-use condition, no prerequisite, and no named alternative such as get_v1_number_profile.

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 supplied, the description carries the full behavioral burden and does so well: it explains null semantics for hidden/absent `about` and `profile_picture_url`, notes picture URL expiry, defines the `unavailable` field for unreadable parts, and specifies the 404 `not_registered` error for numbers without WhatsApp along with the 3-credit billing cost.

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?

Nearly every clause earns its place — field list, null rules, error case, group, billing — and the key purpose is front-loaded. The opening sentence is a heavily nested run-on that is harder to parse than it needs to be, costing a point on 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?

There is no output schema, so the description must describe the return shape, and it does so thoroughly by naming the fields, their nesting (businessProfile sub-fields), and their null/error behavior. An agent has everything needed to call this correctly and interpret the result.

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% on a single `phone` parameter, so the schema already documents format, accepted variants (spaces, dashes, `00` prefix, `14155550123@c.us` form) and an example. The description adds nothing about the parameter, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource: retrieving everything WhatsApp exposes about the account behind a phone number, and enumerates the returned facets (pushname, isBusiness, verifiedName, businessProfile, about, picture URL, LID, device count). This is clearly distinguishable from the sibling check/search/channel tools, which deal with registration status, channels, and groups rather than a number's profile.

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 implies usage (fetch profile metadata for a known WhatsApp number) and the `not_registered` 404 tells the agent what happens for a non-account, but it never states when to prefer this over `get_v1_number_check` or any other sibling, and there are no explicit exclusions or prerequisites.

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