Release Readiness Triage MCP

generate_release_recommendation

Generate a release readiness verdict by combining CI failures, flakiness history, and code changes to output GO, NO_GO, or INVESTIGATE with confidence score and blocker breakdown.

Instructions

The final step: combines failures, flakiness history, and code change correlation to produce a GO / NO_GO / INVESTIGATE verdict with confidence score and a breakdown of blockers vs safe-to-ignore failures.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "failures": "<failures>",
      "flakinessHistory": "<flakinessHistory>",
      "changedFiles": "<changedFiles>"
    },
    "name": "generate_release_recommendation"
  }
}

Input Schema

Name	Required	Description
`format`	No	Output format. Use 'markdown' for GitHub PR comments or Slack. Defaults to 'text'.
`failures`	Yes	All failures from the CI run
`changedFiles`	Yes	Files changed in this commit/PR
`affectedTests`	No	Tests known to be affected by code changes (from ast-impact-mapper-mcp)
`flakinessHistory`	Yes	Flakiness history for cross-referencing
`customInfraPatterns`	No	Extra regex patterns (as strings) to classify as infrastructure errors, e.g. 'GCP quota exceeded', 'No space left on device'

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.2.0Aug 5, 2026

TDQS

A4.2/5.0

Behavior4/5

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

No annotations were provided, so the description bears the disclosure weight. It discloses the combination logic and output structure (verdict, confidence score, blockers vs safe-to-ignore breakdown), which is good transparency for a non-mutating decision tool. It does not describe edge cases or external effects, but for this type of tool the disclosure is adequate.

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 sentence with strong front-loading ('The final step') and no redundant wording. It conveys the tool's purpose, inputs, and outputs efficiently.

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?

Without an output schema, the description explicitly lists the verdict types and breakdown categories, which is necessary for an agent to understand return values. It does not mention how affectedTests or customInfraPatterns factor in, but those are documented in the schema, so the completeness is adequate.

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 coverage is 100% with all parameters described, so the baseline is 3. The description conceptually ties together failures, flakinessHistory, and changedFiles but adds no detail beyond the schema for format, affectedTests, or customInfraPatterns.

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 uses a specific verb ('combines') and resource ('failures, flakiness history, and code change correlation') to produce a distinct output (GO / NO_GO / INVESTIGATE verdict). This clearly distinguishes it from sibling tools that handle individual analyses, and the 'final step' phrasing positions it as the synthesis tool.

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?

Explicitly labels itself as 'the final step', implying it should be used after running the upstream analysis tools. However, it does not explicitly name alternatives or state when not to use it, which keeps it from a perfect score.

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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