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ouroboros_start_execute_seed

Launch seed execution in the background and receive a job ID immediately to track progress and retrieve terminal output later.

Instructions

Start a seed execution in the background and return a job ID immediately. Use ouroboros_ac_tree_hud for live progress snapshots and ouroboros_job_result for terminal output. In plugin mode, execution is delegated to an OpenCode Task pane and job_id is None — results appear in the Task pane instead of being pollable via job_status/job_result. This is the handler for 'ooo run' commands — do NOT run 'ooo' in the shell; call this MCP tool instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cwdNoWorking directory used to resolve relative seed paths.
skip_qaNoSkip post-execution QA evaluation. Default: false
seed_pathNoPath to a seed YAML file. If the path does not exist, the value is treated as inline seed YAML.
model_tierNoModel-tier routing: small/medium/large → frugal/standard/frontier execution tier (trusted decomposed children may run one tier below; retries escalate). Omit to preserve automatic runtime selection; pass medium explicitly to pin standard routing.
session_idNoOptional session ID to resume. If not provided, a new session is created.
auto_evolveNoOverride execution.auto_evolve for the chained evaluation. When true, an explicitly rejected evaluation starts a bounded Ralph continuation loop.
seed_contentNoInline seed YAML content to execute.
auto_evaluateNoOverride execution.auto_evaluate for this call. When true, a completed background execute_seed run enqueues formal 3-stage evaluation as a separate bounded background job.
max_iterationsNoMaximum number of execution iterations. Default: 10
efficiency_modeNoExecution efficiency policy. adaptive may start decomposed ACs on lower-cost tiers and escalate on recovery; quality_first keeps children at the parent starting tier. Default: adaptive.
idempotency_keyNoOptional process-local idempotency key. A second call with the same key returns the same execution metadata and does NOT enqueue a new execution. Map TTL is process lifetime — not persistent across server restarts.
conductor_directiveNoBounded corrective context copied exactly from the selected conductor decision. Fresh successor executions only.
frugality_assuranceNoFrugality assurance: off, lightweight observe, or explicit strict baseline eligibility. Defaults from efficiency_mode; strict is never enabled implicitly.
conductor_decision_idNoSelected conductor decision receipt authorizing a fresh successor.
predecessor_execution_idNoExecution ID that the new successor follows.
Behavior3/5

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

With no annotations, the description carries the full behavioral disclosure burden. It does disclose key runtime behavior: the tool runs in the background, returns immediately, and delegates to a Task pane in plugin mode with job_id=None. However, it does not state whether the operation is mutating, what side effects or permissions are required, or how idempotency_key interacts beyond the schema. This is partial disclosure, not comprehensive.

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 four sentences, each serving a distinct purpose: core action, monitoring pointers, plugin exception, and shell alias warning. It is front-loaded with the primary behavior and uses no filler words. This is exemplary economy.

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

Completeness4/5

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

Despite 15 parameters and no output schema, the description covers the most important context: the async job model, where to find progress/output, the plugin-mode behavioral shift, and the relationship to the 'ooo' shell command. It does not explain return value structure, but no output schema exists and the job_id/None behavior is disclosed. It is complete enough for a high-complexity tool.

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 coverage is 100%, with each of the 15 parameters having meaningful descriptions in the input schema. The tool description itself adds no parameter-specific semantics—it stays at the level of execution mode and monitoring. Per rubric, this hits the baseline of 3.

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

Purpose4/5

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

The description opens with 'Start a seed execution in the background and return a job ID immediately,' clearly identifying the verb (start), resource (seed execution), and immediate outcome (job ID). It also notes it is the handler for 'ooo run' commands, which distinguishes it from a shell command but does not explicitly contrast it with sibling tools like ouroboros_execute_seed. This implicit differentiation prevents a 5.

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

Usage Guidelines5/5

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

The description explicitly directs users to 'Use ouroboros_ac_tree_hud for live progress snapshots and ouroboros_job_result for terminal output,' providing clear alternatives for post-start actions. It also warns 'do NOT run ''ooo'' in the shell; call this MCP tool instead,' a concrete when-not instruction. The plugin-mode caveat further clarifies when job polling is unavailable.

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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