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Get deployments by person

get-deployments-by-person-tool
Read-onlyIdempotent

List who triggered production deployments over a recent window (default 7 days) and how many each shipped, with failed deploys surfaced per person — e.g. "Bob Marley: 5 deploys (3 failed)". Use this to answer "who has deployed to production this week and how much". Returns each person's deploy count, failed count, and the repositories they shipped to, sorted by deploy count, plus team totals.

Input Schema

NameRequiredDescriptionDefault
daysNoHow many days back to count production deploys. Defaults to 7 (this week), clamped to 1–90.

Output Schema

NameRequiredDescriptionDefault
daysYesLookback window in days.
teamYesTeam name.
sinceYesISO-8601 start of the window.
peopleYesPer-person breakdown: deploy_count, failed_count, and repositories, sorted by deploy_count.
environmentYesDeployment environment counted (production).
total_failedYesTotal failed production deploys in the window.
total_deploysYesTotal production deploys across the team in the window.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already establish readOnlyHint and idempotentHint, so the description only needs to add context — and it does: the windowing default, the per-person failure surfacing, the sort order (by deploy count), and the inclusion of team totals. It doesn't mention any rate limits or empty-result behavior, but for a read-only aggregate that's a minor gap.

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

Conciseness4/5

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

Front-loaded with the core action and scope, followed by the use case and return contents. The inline example ('Bob Marley: 5 deploys (3 failed)') earns its place by conveying output shape, though the final sentence partially duplicates the output schema.

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?

For a single-optional-parameter read tool with annotations and an output schema, the description covers purpose, usage trigger, and aggregation behavior. The return-value description is somewhat redundant given the output schema exists, and no sibling differentiation is offered, keeping it just shy of full marks.

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?

There is only one parameter and schema description coverage is 100% — the schema already documents 'days', the default of 7, and the 1–90 clamp. The description restates the 7-day default but adds no new semantics. Baseline 3 applies when the schema does the heavy lifting.

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?

States a specific verb and resource — listing who triggered production deployments over a window, with failed counts and repos per person — and includes a concrete output example. It's clearly distinguishable by topic from get-dora-metrics-tool or get-person-activity-tool, but it never names those siblings to make the boundary explicit.

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?

Gives an explicit usage trigger: 'Use this to answer "who has deployed to production this week and how much".' That's a clear context for selection, but there are no exclusions or pointers to alternatives (e.g. when to use get-dora-metrics-tool instead of this attribution view).

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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