Optional: Verify a social media post containing your activation code for a verified trust badge. Not required for API access — agents are auto-activated on registration.
| Name | Required | Description | Default |
|---|---|---|---|
| post_url | Yes | URL of the social media post containing your activation code | |
| agent_key | Yes | Your registered agent API key (starts with hp_) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral disclosure burden. It adds useful context that the tool is optional and auto-activation occurs, but it does not state whether the operation is read-only, what happens on success, or any potential side effects. The verb 'Verify' implies a read operation, but this is not explicit.
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-loaded with the 'Optional' context, and every clause adds value. There is no fluff or repetition, making it highly 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?
The tool is simple with 2 documented parameters, and the description clarifies its purpose and optionality. However, there is no output schema, and the description does not explain what a successful verification returns or what the 'verified trust badge' entails, leaving a modest gap for agents to understand the post-call outcome.
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?
Both parameters have schema descriptions covering 100% of the inputs, so the description need not add parameter details. It mentions 'activation code' and 'social media post,' which aligns with the schema but does not add new format or syntax beyond 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?
The description uses the specific verb 'Verify' with the resource 'social media post containing your activation code' and states the purpose 'for a verified trust badge.' It clearly distinguishes from sibling verification tools by focusing on social media posts rather than domain or payment verification.
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 explicitly labels the tool as 'Optional' and states 'Not required for API access — agents are auto-activated on registration,' providing a clear when-not scenario. However, it does not explicitly mention alternative tools for other verification types (e.g., verify_agent_domain), so it stops short of full alternative guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have clearly distinct purposes (e.g., get_human vs get_human_profile differ by access level, get_listing vs get_listings by specificity). There is minor overlap between check_humanity_status and get_human (both return verification info), and the deprecated no-op claim_free_pro_upgrade adds slight clutter, but descriptions otherwise disambiguate well.
All 40 tools follow a consistent snake_case verb_noun pattern (e.g., create_listing, get_job_status, start_stream, submit_verdict). No camelCase or mixed conventions exist; even compound actions like make_listing_offer and leave_review fit the established pattern.
With 40 tools, this is far beyond the 16-25 'heavy' range and into the 'too many' category. While the platform covers a broad domain (hiring, listings, streams, escrow, activation), this many tools could be split into smaller focused servers for maintainability and agent selection clarity.
The surface covers the core lifecycle well: search, hire, pay, communicate, approve, review. However, there is no generic cancel_job tool for regular jobs (only stop_stream for streams) and no update_listing to edit an existing listing, leaving small but navigable gaps in lifecycle management.
