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

With no annotations, the description carries the full burden and largely succeeds: it discloses what the check inspects and, crucially, the verdict contract (ok=false means do not publish as-is). It does not state permission/auth needs or whether the check is purely read-only, but the output semantics are a meaningful behavioral disclosure.

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

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

Two sentences, front-loaded with the purpose and followed by the actionable verdict rule. No filler or repetition.

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

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

An output schema exists, so return values need not be explained, and the description usefully clarifies the ok=false semantics. However, the near-total absence of parameter guidance for a 3-param tool with 0% schema coverage leaves a real gap for correct invocation.

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

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

Schema description coverage is 0% for three parameters (text, hashtags, platform), and the description never defines them. It only indirectly hints that hashtags and platform matter via the phrases "hashtag stuffing" and "platform length limits"; it does not explain the platform default of "x" or how hashtags relate to the text field.

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 (risk check for a post) and enumerates exactly what is inspected: prompt leaks, engagement bait, hashtag stuffing, link stacking, platform length limits. This clearly separates it from the sibling generate_posts/save_draft/list_posts 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?

"Pre-publish" gives a clear trigger context for when to call it, and "one post" scopes it to a single item. It does not name an alternative tool or state when not to use it, so it stops short of full routing 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 behavioral burden and does reasonably well: it discloses the 8-stage pipeline, a QA self-critique step, offline vs model-backed execution, and the 1-10 bounds on num_topics. It omits cost, latency, and failure modes, but the environment-dependent execution behavior is an uncommon and valuable disclosure.

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 purpose sentence, then a compact pipeline line and an Args block; each element earns its place. The em-dash/arrow formatting is slightly dense but not wasteful, and nothing is buried.

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?

An output schema exists, so return values need no explanation, and the description fully covers execution model and parameters. The remaining gap is the absence of any routing guidance relative to check_post and save_draft, which prevents a 5 for a tool with four siblings.

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: all six parameters are explained, including the allowed platform values (x, linkedin, instagram, tiktok, youtube, xiaohongshu, wechat), the num_topics range 1-10, the language auto/en/zh options, and the semantics of trends and material. This adds meaning well beyond the bare 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?

The first line gives a precise verb and resource: generate platform-specific social posts from brand material, and the pipeline enumeration (brand DNA → trends → ideation → copy → visual → storyboard → QA) makes the scope concrete. It never references the siblings (check_post, save_draft, list_posts), so differentiation from alternatives is left to inference, which keeps it at 4 rather than 5.

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

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

The description supplies useful operational context — works offline without an API key, uses a real model when configured via YOMINPOST_PROVIDER/ANTHROPIC_API_KEY — but it never says when to reach for this tool versus check_post or save_draft, nor any prerequisite or exclusion. Usage is implied by the pipeline framing rather than stated.

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

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

No annotations are provided, so the description carries the disclosure burden. 'List' implies a safe read operation, and the parenthetical adds that results indicate which channels publish for real and how they authenticate, but there is no statement of auth requirements, rate limits, or side effects (and no output schema caveat beyond the fact one exists).

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 front-loaded sentence with zero filler; the parenthetical adds genuine information about the returned fields rather than restating the 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?

An output schema exists, so return values need not be spelled out, and the description is essentially complete for a zero-argument list tool. The only gap is the absence of any when-to-use routing against its four siblings.

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 the baseline of 4 applies. Schema coverage is 100% and there is nothing for the description to compensate for.

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 ('List') and a concrete resource ('generation targets and publishing channels'), which is clearly distinct from siblings like list_posts or generate_posts. It could sharpen the distinction further by naming when this differs from list_posts, but the resource is unambiguous.

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

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

There is no explicit when-to-use statement or named alternative. Usage is only implied by the phrasing 'generation targets' (i.e., consult this to discover where posts can go), leaving the agent to infer the ordering relative to generate_posts and check_post.

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; 'List' reasonably implies a read-only operation, and the status-filter semantics are genuinely added context beyond the structured fields. However, it says nothing about pagination behavior, ordering, or what happens when limit exceeds available posts.

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, front-loaded with the core purpose and then the status filter semantics. Nothing is padding, though the terse format leaves gaps rather than being excessive.

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?

An output schema exists, so return-value documentation is not required. The main remaining gap is the undocumented limit parameter and absence of any pagination or ordering note, which matters for a listing tool defaulting to 20 results.

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. It documents the status parameter's allowed values ('draft | scheduled | posted | failed') and the empty-string default meaning ('empty = all'), which is real added value, but the limit parameter is left completely unexplained.

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 ('List') and resource ('posts') with a scope qualifier ('in the local workspace'), so the agent knows exactly what it returns. It doesn't differentiate from the sibling listing tool list_platforms or explain its relationship to generate_posts/check_post, but the action is unambiguous.

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

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

No when-to-use guidance, no conditions, no mention of alternatives like check_post for a single post. The purpose is implied by the verb but the agent gets no routing help among the five siblings.

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 disclosure burden. It usefully discloses the key side-effect profile (saved locally, not published) and that channels must already be connected, but says nothing about overwrite/duplicate behavior, what happens with unconnected platforms, 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?

Two sentences, front-loaded with the core action and scope, and the second sentence adds the essential non-publishing clarification. 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?

An output schema exists so return values need not be explained, and the purpose/side-effect profile is adequately covered. However, with 6 undocumented parameters and no annotations, the definition leaves meaningful gaps for an agent assembling a call.

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% across 6 parameters, so the description must compensate and largely does not: only 'platforms' is implied by 'targeting the connected channels for the given platforms.' The hook, cta, hashtags, and title fields are never mentioned, and the only required parameter (text) is not explained.

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 (save) and resource (post as a DRAFT) with an explicit scope: the local YominPost workspace, targeting connected channels for the given platforms. This is clearly distinguishable from siblings like generate_posts, check_post, and list_posts without opening a schema.

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

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

Makes the usage context explicit: the result is not published and the user must review and publish it in the web UI, which tells the agent this is the pre-publish path rather than a publish action. It stops short of naming a sibling alternative (e.g., a publish tool), so it is clear but not fully routing.

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