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deployment_status

Check the current status of a deployment to monitor progress, verify success, or identify failures in Railway.app infrastructure.

Instructions

[API] Check the current status of a deployment

⚡️ Best for: ✓ Monitoring deployment progress ✓ Verifying successful deployments ✓ Checking for deployment failures

⚠️ Not for: × Service runtime logs × Database logs

→ Prerequisites: deployment_list, deployment_trigger

→ Next steps: deployment_logs

→ Related: service_info, service_restart, deployment_wait

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
deploymentIdYesID of the deployment to check status for
Behavior3/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It implies this is a read-only operation ('Check'), but doesn't explicitly state whether it requires authentication, has rate limits, or what the response format looks like. The description adds some context about what it's not for, but lacks details on behavioral traits like error handling or output structure.

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 well-structured and front-loaded, starting with the core purpose, followed by best use cases, exclusions, prerequisites, next steps, and related tools. Each section is concise and adds value, with no wasted sentences or redundant information.

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?

Given the tool's moderate complexity (single parameter, no output schema, no annotations), the description is mostly complete. It covers purpose, usage guidelines, and contextual relationships effectively. However, it lacks details on behavioral aspects like response format or error conditions, which would be helpful since no output schema is provided.

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?

The input schema has 100% description coverage, with the single parameter 'deploymentId' clearly documented. The description doesn't add any meaning beyond what the schema provides (e.g., it doesn't explain where to get the deploymentId or format details). With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't need to.

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's purpose with a specific verb ('Check') and resource ('current status of a deployment'). It distinguishes itself from siblings like deployment_list (which lists deployments) and deployment_logs (which provides logs), making it evident this is a status-checking operation.

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 provides explicit guidance on when to use this tool ('Best for: Monitoring deployment progress, Verifying successful deployments, Checking for deployment failures') and when not to use it ('Not for: Service runtime logs, Database logs'). It also lists prerequisites (deployment_list, deployment_trigger), next steps (deployment_logs), and related tools (service_info, service_restart, deployment_wait), offering comprehensive context for selection.

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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