postcopilot-mcp

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

With no annotations provided, the description carries the disclosure burden. It clearly states the tool returns direct download URLs rather than a file and highlights the no-watermark behavior. It does not cover auth, error handling, or invalid-input behavior, but for a simple download tool this is reasonably transparent.

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 concise sentences each contribute useful information: the action, the output/no-watermark detail, and the input constraint with an example. There is 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?

For a tool with one required parameter and no output schema, the description covers purpose, input requirements, an example, and the return value. It could mention what happens for invalid or non-video posts, but that is a minor gap given the tool's simplicity.

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 already documents the url parameter at 100% coverage, giving a baseline of 3. The description adds value by requiring that the post contain a video and by providing an example URL, which helps the agent understand the expected input format beyond 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?

The description names a specific action (download), a specific resource (video from a Threads post URL), and the output type (direct video download URLs). It is clearly distinguishable from sibling tools, which focus on exports, profile reading, or post generation.

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 gives clear context for use: it applies when given a Threads post URL that contains a video, and it includes a concrete URL example. It does not explicitly list excluded cases or alternatives, so it falls short of a 5.

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

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

With no annotations provided, the description carries the behavioral burden. It discloses the export limit, the exact returned fields, and the required URL format. It stops short of mentioning auth, rate limits, or failure cases, but for this simple export tool the core behavior is transparent.

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 with no filler: the verb and resource are front-loaded, and every clause adds useful information—the cap, returned fields, and URL format.

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?

Since there is no output schema, the description compensates by naming the return fields. It fully specifies the single required parameter and its format. Minor contextual gaps exist around public-profile requirements or edge cases, but nothing essential for calling the tool is missing.

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 the schema already documents the url parameter with the same example. The description's URL reminder adds little semantic depth beyond what the input schema already provides.

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 opens with an explicit action (Export), object (followers), source (Threads user profile), and a concrete cap (up to 60). It also lists the returned fields, making it clearly distinguishable from siblings like postcopilot_export_following and postcopilot_export_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?

It clearly tells the agent what input to provide—a Threads profile URL—and gives an example format. It does not explicitly name alternatives or exclude cases, but the follower-specific wording provides sufficient routing context.

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 burden of behavioral disclosure. It does disclose the 60-account limit and the return fields, which is useful. However, it does not explicitly state that the operation is read-only (though 'export' implies this), nor does it mention authentication requirements, rate limits, or any potential side effects. Given the lack of annotations, this is a moderate 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?

The description is two sentences, front-loads the core action and limit, lists the return fields, and provides a concrete URL example. Every word earns its place with no redundancy or fluff.

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 tool with one parameter and no output schema, the description covers the purpose, the limit, the return fields, and an example. It does not explicitly mention prerequisites like authentication or clarify whether the 60-account cap implies truncation or pagination, but these are minor gaps. Overall, an agent can invoke it correctly with the given information.

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% since the single 'url' parameter already has a description with an example. The tool description reinforces the same example but adds no new semantic meaning beyond the schema. Thus, the baseline of 3 is appropriate; the description does not compensate for any coverage gap because there is none.

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

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

The description clearly states the tool exports up to 60 accounts a Threads user follows, and lists the specific return fields (usernames, display names, follower counts, verification status). It uses a specific verb and resource and implicitly distinguishes from siblings like export_followers (followers vs following) and export_profile (profile info).

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 explains what the tool does and provides an example URL, but it does not explicitly state when to use this tool over the sibling export_followers or other alternatives. There is no mention of 'use this to get who a user follows' or a directive to choose the follower tool for the reverse. The context is clear but the routing guidance is implied rather than explicit.

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 adds meaningful behavioral info: it limits output to 'up to 20 recent posts' and enumerates the returned structured fields. It doesn't discuss authentication or error behavior, but for a read-style scrape this is decent coverage beyond a bare 'Export posts' statement.

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: the first states the main action, the second supplies return details and an example. No filler or redundant framing.

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 single parameter is fully documented by the schema, and the description outlines the expected return fields even though there is no output schema. It does not acknowledge whether the profile must be public or whether only the latest 20 posts are available, but it is sufficient for the requested simple task.

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 already has a full parameter description (100% coverage) with the same example URL. The tool description's sentence 'Provide a profile URL like...' repeats the schema and adds no additional semantic nuance needed to call the tool correctly.

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 ('Export up to 20 recent posts from a Threads user profile') and distinguishes itself from sibling tools that export followers or following. The return fields (text, likes, replies, reposts, timestamps) further confirm what the tool produces, leaving no ambiguity.

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 provides clear context that this tool is for profile posts, and includes a typical URL format. However, it does not explicitly mention alternatives or exclusions, such as using postcopilot_export_followers for follower lists. The guidance is implied rather than spelled out for the 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?

With no annotations provided, the description carries the burden. It does disclose the main behavior—generating text from a topic—and says the result is a caption. However, it never explicitly states that it only generates text and does not publish to Threads, and it overpromises 'viral' with no qualification.

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 sentences and front-loads the core action. It avoids repetition of schema contents and communicates the key input-output expectation efficiently.

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

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

Given the tool has only two parameters, a single required one, and no nested schema, the description covers the critical elements: input prompt, model usage, and return type. The absence of an output schema is mitigated by 'Returns the generated text,' which is sufficient for this kind of generation tool.

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 covers both parameters at 100%, so the baseline is 3. The description adds the phrase 'topic or idea,' mapping directly to 'message,' but it does not explain the 'model' parameter or how to select between 'gpt' and 'llama' beyond the schema's own enum description.

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

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

The description uses a specific verb ('Generate') and resource ('Threads post') and identifies the core mechanism ('fine-tuned AI model'). It clearly differentiates this from siblings like download/export by stating the task is to produce a caption.

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 gives practical usage context: provide a topic or idea and receive a ready-to-post result. It does not explicitly list when not to use the tool, but the contrast with read/export/download siblings makes the intended use fairly evident.

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 burden. It discloses that the tool returns full text content and supports two input modes (catalog discovery or topic search). Missing are details on failure behavior, output formatting, and any auth/network requirements, but for a read-only tool the disclosed behavior is reasonably adequate.

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 purpose and return type, followed by usage guidance. Every phrase earns its place and 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?

The tool is simple (one required parameter, no output schema, no nested objects), and the description covers core behavior, return value, and discovery workflow. Minor gaps like failure behavior and exact output formatting keep it from a 5, but for the tool's complexity it is largely 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?

The schema already fully documents the single 'topic' parameter with examples and the slug alternative (100% coverage), so the baseline is 3. The description adds value by recommending the catalog resource first to find valid slugs, which slightly enriches parameter guidance, but does not fundamentally extend what the schema already provides.

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 'read' and resource 'PostCopilot blog post/guide about Threads', and immediately clarifies the return value ('Returns the full text content'). This clearly differentiates from sibling tools, which are all distinct actions like download_video, export_followers, and generate_post.

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 explicit workflow guidance: use the postcopilot://blog/catalog resource first to see available guides, or provide a topic to search. This tells the agent how to discover valid input values. It doesn't explicitly name alternatives to exclude, but sibling tools are all obviously different actions, so no exclusion is necessary.

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