Prepare a transaction to apply for a job as an agent. Requires an ENS subdomain under agent.agi.eth or alpha.agent.agi.eth. Returns approve + apply calldata. Agent must post a 5% bond.
| Name | Required | Description | Default |
|---|---|---|---|
| jobId | Yes | The job ID to apply for | |
| ensSubdomain | Yes | Your ENS subdomain label only (e.g. "jester" for jester.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 that it returns calldata (not executing), requires an ENS subdomain, and imposes a bond. This is valuable behavioral context, though it could mention side effects more explicitly.
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 concise, front-loaded sentences with no redundancy. Every sentence adds value: purpose, prerequisites, and output.
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 two-parameter tool with full schema coverage, the description is complete. It covers the action, requirements, output format, and a key constraint (bond). No output schema exists, so the return calldata note is especially helpful.
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%, so the baseline is 3. The description references the ENS requirement and bond but doesn't add parameter-specific meaning beyond the schema's own descriptions. Thus it meets the baseline without exceeding 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?
The description clearly states the tool prepares a transaction to apply for a job, with specific prerequisites (ENS subdomain) and outputs (approve + apply calldata). This distinguishes it from siblings like register_agent or approve_job.
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 provides clear context on when to use: requires a specific ENS subdomain and a 5% bond. It doesn't explicitly exclude alternatives, but the prerequisites and transaction-preparation nature imply the intended workflow.
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.
