Claw Post

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explains that the post is queued (not immediate), that the browser extension picks it up, that a jobId is returned, and that polling is required. It also details the media upload prerequisite. This is comprehensive transparency for an asynchronous operation.

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 paragraph but well-structured: it starts with the core purpose, then explains the return value and polling, and finally the media upload step. It is concise without being terse, and every sentence adds necessary information. It could be slightly more scannable, but it is efficient.

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's complexity (5 parameters, nested objects, no output schema), the description covers the essential flow: queueing, polling, media handling, and return values. It lacks explicit error-handling or edge-case guidance, but it provides enough for an agent to call the tool and interpret results correctly. The absence of an output schema is mitigated by the description of jobId and postUrl.

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 explain parameters. It covers text, platform, and mediaPaths (via the upload flow), but it does not mention idempotencyKey or platformPayload. These parameters are left unexplained, which is a gap for an agent trying to use them correctly. The description adds value for some parameters but not all.

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's function: 'Queues a social post for the user.' It specifies the resource (social post) and the action (queue), and it distinguishes itself from sibling tools like create_reddit_comment by focusing on social posts. The mention of the browser extension and jobId further clarifies its unique purpose.

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 explicit workflow instructions: poll get_post_status with the jobId until a terminal status, and call get_upload_url first for media. It clearly tells the agent when to use this tool and how to chain it with siblings, leaving no ambiguity about the required follow-up steps.

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. It discloses async queuing, execution via the user's Chrome, no API/credentials, return of a jobId, success permalink, and user prerequisites. This is comprehensive 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?

The description is dense but every sentence adds information: mechanism, URL constraint, no-API distinction, async behavior, polling target, success output, and prerequisites. 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 3-param tool with no output schema and no annotations, it explains mechanism, prerequisites, async polling, and return values. The only meaningful gap is the undocumented idempotencyKey, which prevents full completeness.

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 has 0% description coverage, so the description must compensate. It adds meaning for targetUrl (must include /comments/) and text (reply text), but idempotencyKey is never mentioned and its purpose is left to the agent to infer.

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 a specific verb and resource: 'Queues a Reddit comment/reply'. It also disambiguates from siblings by explicitly stating it does not use the Reddit API and runs via the paired Claw Post extension, making it clear this is a comment action rather than create_post or get_post_status.

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

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

It gives explicit prerequisites (logged-in Chrome, paired extension, Chrome open), a URL constraint (must include /comments/), and directs polling with get_post_status. It does not explicitly contrast with create_post, but the comment-versus-post distinction is strongly implied by the title and 'comment/reply' language.

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 disclosure. It reveals that the response contains pairedExtension, pairingUrl, current usage, and connected devices, and defines the branch behavior when pairing is false. It doesn't cover auth/rate limits, but for a read-type status call this is solid.

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, front-loading the return value first and the workflow guidance second. Every sentence contributes operational value.

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

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

For a simple one-parameter status tool with no output schema, the description covers the main response content and calling context well. The main gap is the undocumented returnTo parameter, so it isn't fully 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%, and the description never mentions the single optional returnTo parameter. The schema offers only a name and URI format, leaving the agent without any explanation of what the parameter does or when to pass it.

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?

Description states a specific verb ('Returns') and resource (account status: paired browser extension, current usage, connected devices), and ties it to a concrete next step ('Use this BEFORE create_post'), which differentiates it from siblings like get_post_status.

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

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

Explicitly instructs 'Use this BEFORE create_post' and provides a conditional action ('if pairedExtension is false, surface pairingUrl to the user'). It doesn't mention when not to use it or compare with alternatives, so it falls just short of the most explicit bar.

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?

Since no annotations are provided, the description carries the full burden; it discloses that the tool returns status, and it enumerates the expected fields on success (postUrl) and failure (error, errorCode). It implies a read-only polling behavior, though it does not explicitly state auth, rate limits, or a no-side-effects guarantee.

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 three sentences, each earning its place: it states the function, the polling workflow, and the key result flags. It is front-loaded with the core action and contains no filler or redundancy.

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 polling tool, the description adequately covers the main return fields and terminal statuses. However, it does not mention intermediate statuses (e.g., queued, processing) or polling cadence/timeout, and with no output schema these details are absent. This is a notable gap but not 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?

The schema has 0% description coverage, so the description must compensate. It adds context by tying the tool to create_post, implying jobId comes from that flow, but it never explicitly states that jobId is the identifier returned by create_post or describes its format. This is partial compensation, not full.

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

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

The description states the specific verb and resource: 'Returns the current status of a post job.' It further differentiates itself from siblings by referencing the create_post flow and focusing on queued/completed post status, which is clearly distinct from creation tools or account status.

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

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

The description gives explicit usage guidance: 'Poll this after create_post until status is succeeded or failed.' It also explains how to use the result on success and failure. It does not explicitly list when-not alternatives, but the trigger condition is clear and sufficient for tool 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 provided, the description fully carries the behavioral disclosure burden. It reveals that the URL is signed, will reject with 403 on incorrect headers, requires no auth header on the PUT, and that contentType is inferred if omitted. It also explains failure behavior for unsupported platforms and instructs not to proceed to create_post on PUT failure.

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 longer than average but every sentence earns its place, covering purpose, step-by-step usage, and critical security behavior. It front-loads the core purpose and then structures the upload flow clearly, with only a minor intentional repetition of the header requirement for emphasis.

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 no output schema and no annotations, the description is notably complete: it names the returned artifacts (uploadUrl, putHeaders, read url), explains the 24-hour validity, gives the required header semantics, and specifies the exact three-step calling sequence. An agent has enough information to call the tool and integrate with create_post 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 0%, so the description must compensate, and it largely does: it explains filename extension drives content-type inference, contentType is optional, and platform enables early unsupported-file validation. However, bytes is not addressed at all, which leaves one parameter without added meaning.

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 returns a signed PUT URL for direct media upload to storage and a 24-hour read URL for use with create_post. It identifies the specific verb, resource, and integration point, distinguishing it from sibling tools like create_post and get_account_status.

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

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

The description provides an explicit step-by-step workflow: call this tool, PUT to uploadUrl with exact headers, then pass the returned url to create_post only on success. It also explains when to pass platform for early validation and warns against calling create_post if the PUT fails, though it does not mention alternative upload tools or explicit 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?

There are no annotations, so the description carries the full burden. The word 'Returns' implicitly suggests a read-only operation, but the description does not explicitly state that there are no side effects, nor does it mention authentication, caching, or response format. Acceptable for a zero-parameter list, but not richly 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?

The description is a single, front-loaded sentence with no filler. Every word contributes to the meaning, making it concise and easy to parse.

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 zero-parameter list with no output schema, the description is nearly complete: it states what the tool returns. It could go slightly further by noting the intended use before create_post or clarifying that no input is required, but these are minor gaps.

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 has zero parameters and the schema description coverage is effectively 100%. The baseline of 4 applies, and the description correctly adds no unnecessary parameter detail.

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 ('Returns') and a concrete resource ('social platforms available for posting through Claw Post'). It clearly identifies the tool's purpose and distinguishes it from the sibling create/get/status tools.

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

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

The description implies this is a discovery tool to check which platforms are available before posting, but it does not explicitly state when to use it or contrast it with siblings like create_post. Usage is inferable but not directly guided.

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