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Rollback Project

rollback_project
Destructive

Rollback a project to a previous version. ⚠️ WARNING: This reverts schema AND code to the specified commit. Database data is NOT rolled back. Use get_version_history to find the commit SHA of the version you want to rollback to. After rollback, use get_job_status to monitor the redeployment. Rollback is useful when a schema change breaks deployment. One operation runs on a project at a time: while another runs, the call is refused and the refusal names the running job; wait for it with get_job_status, then call again. While RationalBloks is being updated, the call is refused with 'RationalBloks is being updated': call it again in a few minutes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
versionYesCommit SHA or version to rollback to
project_idYesProject ID (UUID)
environmentNoEnvironment: staging or production (default: staging)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior5/5

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

Beyond the destructiveHint annotation, the description discloses precisely what is reverted (schema and code) and what is not (database data), plus operational behavior: one project operation at a time, refusal messages naming the running job, and temporary refusal during RationalBloks updates. This is rich behavioral context that materially improves safe invocation.

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 front-loaded with the core action and a prominent warning, then proceeds through prerequisites, post-rollback monitoring, use case, concurrency, and service-update behavior. Every sentence conveys operationally relevant information with no filler.

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?

For a destructive, non-idempotent mutation with no output schema, the description supplies the prerequisite tool, the post-action monitoring tool, side-effect boundaries, and concurrency/error behavior. An agent has enough to decide when and how to call it safely.

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 100%, so all three parameters are already documented. The description reinforces the version parameter as a commit SHA but adds no syntax, constraints, or environment semantics beyond the schema, matching the baseline for full schema coverage.

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 a specific verb and resource: 'Rollback a project to a previous version,' and specifies the scope as schema AND code while excluding database data. It does not explicitly differentiate this tool from the sibling rollback_graph_project, so it falls short of 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 Guidelines4/5

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

It gives clear workflow guidance: use get_version_history to find the target SHA, then get_job_status to monitor redeployment, and states the primary use case of recovering from schema changes that break deployment. It lacks explicit when-not-to-use guidance or direct comparison to the sibling rollback_graph_project.

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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