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Start agy job

agy_start

Start a new agy job asynchronously and get an immediate job ID, policy summary, and permission blockers. Use dry run to validate config and policy without spending quota.

Instructions

Begin a new agy job. Returns job_id immediately; never blocks — plus policy_summary and blockers[] for what the profile ceiling did to your permissions request. Use dry_run to resolve config and policy without spawning agy or spending quota.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cwdNoWorkspace directory. Must be inside the project root. Defaults to the project root.
modeNoagy execution mode, e.g. accept-edits or plan.
modelNo
effortNo
promptYesTask for the agent. Sent as --print=<prompt>.
dry_runNoResolve configuration and policy without spawning agy. Costs no quota.
profileNoPermission profile ceiling. research_readonly cannot write or run interpreters. Defaults to research_readonly.
on_denialNoWhat to do on the first policy denial. Default continue.
session_idNoContinue an existing agy conversation. Omit to create a new session.
timeout_msNo
json_schemaNoPath to a JSON schema for structured output.
permissionsNoNarrowing only. allow is intersected with the profile ceiling; deny always wins.
requested_byNo
session_modeNooneshot closes stdin after the prompt; session keeps it open for agy_send.
parent_task_idNo
idle_timeout_msNosession_mode "session" only. Closes stdin (ending the process) after this many ms of no agy_send following the last completed turn. Does not affect timeout_ms/deadline_at — agy_send never extends those. Ignored for oneshot.
expected_artifactsNoWorkspace-relative paths that must exist afterwards. Missing ones block verified_success.
Install Server

TDQS

A4.5/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description discloses key behaviors beyond the openWorldHint annotation: it returns job_id immediately, never blocks, and includes policy_summary and blockers[] in the response. It also explains that dry_run avoids spawning and quota usage. This gives the agent a clear model of the tool's execution and side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences, each carrying essential information: purpose, behavior, and dry_run alternative. It is front-loaded with the core action and avoids any filler or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (17 parameters, no output schema), the description provides crucial return-value context (job_id, policy_summary, blockers[]) that would otherwise be unknown. It also clarifies the non-blocking nature and cost behavior, covering the main aspects an agent needs for correct invocation and expectation setting.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 71%, so the schema already documents most parameters. The description adds general context about the job start flow but does not elaborate on the undocumented parameters (e.g., mode, model, requested_by, parent_task_id). It does not significantly augment the schema descriptions, so a baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description begins with a specific verb and resource: 'Begin a new agy job.' It clearly differentiates this from sibling tools by noting immediate return and non-blocking behavior, and it contrasts with dry_run. This makes the tool's purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives explicit guidance on when to use dry_run versus actually starting a job, including the cost/quota implication. It implies the primary use case is starting a new job, but it does not explicitly contrast with continuing via sibling tools like agy_send or when to use session_id. Still, it provides sufficient context for typical invocation.

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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