check_agent_identity
Check whether a wallet address has already registered an Alpha Agent Identity NFT, and what payout percentage they qualify for.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| address | Yes | Ethereum wallet address to check |
Check whether a wallet address has already registered an Alpha Agent Identity NFT, and what payout percentage they qualify for.
| Name | Required | Description | Default |
|---|---|---|---|
| address | Yes | Ethereum wallet address to check |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the transparency burden. The verb 'check' implies read-only behavior, and the description discloses the return information (registration status and payout percentage). However, it does not explicitly state that the operation has no side effects or require any permissions.
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 concise sentence with no redundant information.
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 query tool with one parameter and no output schema, the description adequately explains what the tool checks and what it returns. No major 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 schema provides a description for the 'address' parameter with 100% coverage, so the baseline is 3. The tool description adds no additional parameter semantics beyond what the schema already states.
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 a specific action ('Check whether...') and a specific resource ('Alpha Agent Identity NFT registration'), plus the additional result (payout percentage). This distinguishes it from sibling tools like register_agent and get_agent_reputation.
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 the use case (checking registration status) but does not explicitly say when to use this tool vs alternatives, nor any exclusions or prerequisites.
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.
Each tool has a distinct purpose with clear boundaries: job lifecycle (create_job, apply_for_job, cancel_job, request_job_completion, finalize_job, expire_job), validation (approve_job, disapprove_job, dispute_job), metadata handling (fetch_job_metadata, upload_to_ipfs), and queries (list_jobs, get_job, get_agent_reputation, check_agent_identity, get_protocol_info, register_agent). No overlapping functionality exists.
All 17 tools follow a consistent snake_case verb_noun pattern (e.g., create_job, list_jobs, fetch_job_metadata). The naming is highly predictable, with verbs like create, get, list, apply, approve, cancel, check, upload, and register consistently paired with relevant nouns.
17 tools is well-scoped for a job management platform covering the full lifecycle from creation to completion, including validation, disputes, metadata handling, and queries. Each tool earns its place, with no redundancy, and the count aligns with the complexity of the domain.
The toolset provides complete coverage for the AGI Alpha job platform: full CRUD/lifecycle (create, list, get, apply, cancel, complete, finalize, expire), validation workflows (approve, disapprove, dispute), identity and reputation management (register_agent, check_agent_identity, get_agent_reputation), metadata handling (upload_to_ipfs, fetch_job_metadata), and protocol info. No gaps are apparent.