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delimit_deploy_verify

Probes health of a newly deployed revision to confirm it is healthy before finishing the deploy. If unhealthy, triggers rollback.

Instructions

Probe a freshly-deployed revision's health — experimental (Pro).

When to use: immediately after delimit_deploy_publish has rolled out a new revision, to confirm the new SHA is actually healthy before declaring the deploy done and closing out the chain (delimit_deploy_verify -> delimit_evidence_collect -> delimit_ledger_done -> delimit_notify). If this returns unhealthy, the next step is delimit_deploy_rollback. When NOT to use: for steady-state runtime health checks (use delimit_obs_status / delimit_obs_metrics), to read deploy-system metadata only (delimit_deploy_status), or for a smoke test before deploy (delimit_test_smoke).

Sibling contrast: delimit_deploy_status reads deploy-system metadata only; this actively probes the running deployment. delimit_obs_status is the steady-state observability surface; this is post-deploy-only.

Side effects: gated by require_premium — unlicensed callers receive a license payload and no probe runs. On a licensed call, invokes backends.deploy_bridge.verify which performs network health checks against the deployed app (HTTP probes, container inspection, dependency reachability). No write. Marked EXPERIMENTAL — health logic may return partial results on backends without health endpoints; do not treat as authoritative for runtime SLOs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
appNoApplication name.
envNoTarget environment ("staging" or "production").
git_refNoOptional git ref the deploy targets.

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: license gating, premium requirement, network health checks, no writes, and experimental status with potential partial results. This exceeds basic behavioral disclosure.

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?

Well-structured with clear sections (purpose, when to use, not to use, sibling contrast, side effects). Front-loaded with core action. Every sentence adds value without redundancy.

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 presence of an output schema, the description does not need to explain return values. It covers usage context, side effects, experimental status, and alternatives comprehensively for a health probe 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% and schema already describes each parameter. The description does not add new semantic details beyond what the schema provides, so baseline 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 clearly states the tool probes a freshly-deployed revision's health, with specific verb and resource. It distinguishes itself from siblings like delimit_deploy_status and delimit_obs_status.

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?

Explicitly states when to use (immediately after delimit_deploy_publish), when not to use (steady-state checks, metadata reads, pre-deploy smoke tests), and provides specific sibling alternatives and next steps for unhealthy results.

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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