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Deploy project pipeline

deploy_project_pipeline

Deploy or rollback a project pipeline to a specified environment. Reuse a built artifact to promote or roll back without rebuilding, and wait for human approval if required.

Instructions

Execute a project-level pipeline deploy or rollback through the local agent.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
env_nameYes
host_idsNoCanonical non-self Host.id values returned by list_hosts; do not pass host names.
variablesNo
project_idNo
pipeline_idYes
project_nameNo
approval_tokenNo
artifact_versionNoReuse an existing built artifact instead of building fresh. Empty = normal deploy (build then deploy). Set it to deploy an existing artifact version to env_name, which SKIPS the build phase and runs deploy+finally only. This powers both rollback (redeploy an old version) and promotion (deploy the artifact a test run produced into prod with prod's variables and deployment targets).
debug_session_idNo
approval_wait_secondsNoMax seconds to block-wait for human approval before returning. 0 = do not wait. Capped at 300.
Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It mentions 'deploy or rollback' but does not disclose side effects, approval requirements (despite approval_token and approval_wait_seconds parameters), blocking behavior, or that it skips build when artifact_version is set. This is a significant gap for a mutation-like operation.

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

Conciseness3/5

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

The description is a single concise sentence, front-loaded with the core action. However, it is under-specified for a tool with 10 parameters and complex behavior, so the brevity comes at the cost of completeness, but it is not a mere tautology.

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

Completeness2/5

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

Given the tool's complexity (10 params, no output schema, no annotations), the one-line description is inadequate. It does not explain return values, approval flow, side effects, or how it interacts with artifacts and debug sessions. The schema partially covers some parameters but does not make the description complete.

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

Parameters2/5

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

Schema description coverage is low (30%), so the description must compensate, but it does not. While the schema itself provides useful descriptions for host_ids, artifact_version, and approval_wait_seconds, the remaining 7 parameters are undocumented except for names, and the tool description adds no parameter semantics.

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 clearly states the tool executes a project-level pipeline deploy or rollback, using a specific verb and resource. It distinguishes from siblings like validate_project_pipeline and upsert_project_pipeline by focusing on execution, though it doesn't explicitly contrast them.

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?

The description provides no guidance on when to use this tool versus alternatives, nor any prerequisites or exclusions. The artifact_version parameter description hints at rollback/promotion use cases, but the tool description itself is silent on usage context.

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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