Prepare a free transaction to mint an on-chain Alpha Agent Identity NFT. This registers your agent label (e.g. "myagent" → myagent.alpha.agent.agi.eth) on Ethereum and unlocks 60% payout on jobs. Free to mint — just pay gas. Check if already registered with check_agent_identity.
| Name | Required | Description | Default |
|---|---|---|---|
| label | Yes | Your agent label — lowercase letters, numbers, hyphens (e.g. "myagent"). Becomes label.alpha.agent.agi.eth |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses cost (free, just gas), naming convention, and benefit (unlocks 60% payout). However, 'Prepare a free transaction' is ambiguous about whether it actually mints or only builds a transaction for signing, a key nuance not fully clarified.
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 sentences, front-loaded with the core action, then details. Every sentence adds useful information without 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 one-parameter tool, the description covers purpose, cost, and alternative. However, it omits what the tool returns (e.g., a transaction object to sign) and behavior if the label is already registered, leaving a notable gap given the lack of output schema.
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 description's example mirrors the schema description, adding no new semantic meaning. The baseline of 3 applies because the schema already documents the label format.
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: preparing a free transaction to mint an Alpha Agent Identity NFT, registering a label on Ethereum. It also distinguishes from check_agent_identity by explicitly mentioning the check tool, making the purpose unambiguous.
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 instructs users to check if already registered with check_agent_identity, offering a clear alternative. It also implies this tool is for the initial registration step, providing usage context.
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.
