Fetch recent Vercel or GitHub deployments with state, commit SHA, branch, and timestamp to correlate releases with incidents and speed root cause analysis.
Fetch recent deployments from Vercel (or GitHub) with deployment state, commit SHA, branch, and timestamp.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max deployments to retrieve (default: 5) | |
| project | No | Project slug or ID | |
| environment | No | Target environment (default: production) |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. It usefully discloses the return payload fields, which substitutes partially for a missing output schema, but says nothing about auth requirements, rate limits, pagination, sort order, or whether results are cached vs live; worse, the '(or GitHub)' hedge leaves the actual data source ambiguous for a write-free read tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single front-loaded sentence with no filler: verb first, resource second, returned fields last. Nothing in it is redundant with the schema, so every clause earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a three-optional-parameter read tool with no output schema, listing the return fields is genuinely helpful. However, with no annotations and no output schema, the description should still cover the source ambiguity, ordering, and any result-shape caveats, none of which appear.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so limit, project, and environment are already fully documented in the schema, and the description adds no parameter-level detail beyond implying recency. Baseline of 3 is appropriate when the schema does all the semantic work.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description gives a specific verb (Fetch) and resource (deployments) plus the returned fields (state, commit SHA, branch, timestamp), so the agent knows exactly what comes back. It does not differentiate itself from close siblings such as get_deployment_logs or compare_deployments, which is the only missing piece for a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no statement of when to use this tool versus alternatives; the sibling list contains get_deployment_logs, compare_deployments and get_deployment_logs, all of which overlap with deployment inspection. The hedging 'from Vercel (or GitHub)' further leaves the agent unsure which source will be queried, but no routing guidance is offered.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.