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ecosystem_deep_review_request

Queue a deep review for a repository, set priority and timeout, and dispatch a sub-agent prompt.

Instructions

Queue a deep-review for a repo and return the dispatch prompt.

Creates an EcosystemDeepReview row queued on the funnel (stage_status='queued'; the legacy status column is a derived read-only view and returns 'queued' — no more 'running'), and embeds a sub-agent prompt (5-section template

  • repo metadata) in the row's dispatch_prompt field. A background watchdog advances stage_status to shallow_failed (status derives to failed) after timeout_minutes if no report has been linked. The Leader is responsible for actually spawning the sub-agent (via TeamCreate/Agent tool with team_name=ecosystem-platform).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repo_idYesEcosystemRepoProfile.id of the target repo.
agent_idNoOptional pre-assigned agent identifier.
priorityNomedium / high / critical (informational only).medium
timeout_minutesNoHard cap before auto-fail (5..180).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

With no annotations provided, the description fully discloses side effects: creates a row, sets stage_status, embeds a dispatch prompt, and includes a watchdog timeout auto-fail behavior. It also clarifies a legacy column derivation.

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

Conciseness4/5

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

Four sentences with front-loaded main action. Each sentence adds value, though a minor reduction could be made without loss.

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 complexity (queuing, watchdog, sub-agent spawning) and presence of an output schema, the description covers all needed behavioral details and lifecycle steps.

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%, so baseline is 3. The description does not add meaning beyond the schema (e.g., repo_id, timeout_minutes constraints are already in the schema description).

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 specifies an action ('Queue a deep-review'), a resource ('for a repo'), and an outcome ('return the dispatch prompt'). It clearly distinguishes from sibling tools like ecosystem_deep_review_cancel or ecosystem_deep_review_list.

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

Usage Guidelines2/5

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

No explicit guidance on when to use this tool versus alternatives (e.g., ecosystem_deep_review_request_batch). The description mentions leader responsibility but does not state prerequisites or exclusions.

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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