cancel_job
Prepare a transaction to cancel an open (unassigned) job. Only the employer can cancel. Escrow is returned.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| jobId | Yes | The job ID to cancel |
Prepare a transaction to cancel an open (unassigned) job. Only the employer can cancel. Escrow is returned.
| Name | Required | Description | Default |
|---|---|---|---|
| jobId | Yes | The job ID to cancel |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the 'prepare a transaction' behavior (cancellation may not be immediate), the permission requirement ('Only the employer can cancel'), and the consequence ('Escrow is returned'). This gives meaningful behavioral insight, though it does not detail the transaction structure or next steps.
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, front-loaded with the primary action, followed by two essential qualifiers. Every sentence adds valuable information with no redundant or filler content.
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 tool with one parameter and no output schema, the description covers purpose, restrictions, and side effects. However, 'Prepare a transaction' is slightly ambiguous and could benefit from mentioning what is returned or how to finalize the cancellation, but the overall context is sufficient.
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 full coverage for jobId with the description 'The job ID to cancel.' The tool description adds no extra parameter semantics beyond contextualizing the job as open/unassigned, which does not change the meaning of jobId. Thus, score is at baseline.
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 action: 'Prepare a transaction to cancel an open (unassigned) job.' It specifies the resource (job), the scope (open/unassigned), and the actor restriction (only employer can cancel), which distinguishes it from sibling tools like approve_job or disapprove_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?
The description provides clear context for when to use this tool: it is for canceling an open unassigned job and only the employer can do it. This implies it should not be used for assigned jobs or by non-employers, though it does not explicitly name alternative tools or scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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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.