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get_deployment_logs

Retrieve detailed logs for a deployment to identify and fix errors. Supports filtering by error, warning, or all log types across Vercel, Netlify, and Cloudflare Pages.

Instructions

Fetch detailed logs for a specific deployment, useful for debugging failed deployments

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tokenNoAPI token for authentication (optional if set in environment)
filterNoFilter logs by type (default: error)error
projectNoProject/site name (required when using 'latest' as deploymentId)
platformYesThe deployment platform
deploymentIdYesThe deployment ID or 'latest' for most recent
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It omits behavior such as authentication requirements (token parameter), default filter behavior (error), and the special 'latest' deploymentId handling that requires a project. The description only says 'Fetch detailed logs', leaving significant behavioral context undisclosed.

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 a single, front-loaded sentence with no filler. It states the action and purpose efficiently. Every word earns its place.

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?

There is no output schema and no annotations, so the description should explain return values or constraints. It does not mention that logs are filtered by default, that 'latest' requires a project, or the structure of the log output. This is inadequate for a tool with 5 parameters and multiple platforms.

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 parameters have their own descriptions. The tool description adds no extra meaning beyond schema; e.g., 'specific deployment' aligns with deploymentId but does not clarify the 'latest' option or filter defaults. Baseline 3 applies because the schema already documents parameters adequately.

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 verb 'Fetch' and the resource 'detailed logs for a specific deployment'. It distinguishes this from siblings like check_deployment_status (status) and compare_deployments (comparison) by focusing on log retrieval for debugging.

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

Usage Guidelines3/5

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

The phrase 'useful for debugging failed deployments' implies when to use it, but it does not explicitly mention alternatives or when not to use it. Sibling tools exist (watch_deployment, check_deployment_status) but are not referenced, so the guidance remains implicit rather than directive.

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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