Check the humanity verification status for a specific human. Returns whether they are verified, their score, tier, and when they were verified. This is read-only.
| Name | Required | Description | Default |
|---|---|---|---|
| human_id | Yes | The ID of the human to check |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full burden. It explicitly states the operation is read-only and details the return data (verified, score, tier, timestamp). However, it does not cover error cases (e.g., invalid human_id) or other side effects, making it adequate but not comprehensive.
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 concise sentences, each serving a clear purpose: stating the main action, listing the return values, and noting the read-only nature. There is no redundancy or filler, and the key action is front-loaded.
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 one required parameter, no output schema, and no annotations. The description sufficiently covers the return values and side-effect profile (read-only). It omits details like error behavior or score scale, but given the low 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 input schema already provides a full description for human_id ('The ID of the human to check') with 100% coverage. The description only reinforces this by saying 'for a specific human,' adding no additional semantic information. Baseline 3 applies per the rubric.
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 checks humanity verification status for a specific human, and it enumerates the returned fields (verified, score, tier, when verified). This specific verb+resource combination distinguishes it from broader sibling tools like get_human or get_human_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 makes it evident that this tool is for checking a specific human's verification status, providing clear context. However, it does not mention exclusions or alternatives, such as when to use get_human instead, so it lacks explicit alternative guidance but is still clear.
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.
