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TypeScript
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Generate Playwright test from report

test_gen_from_report

Turn a classified bug report into a Playwright regression test and open a draft GitHub PR to lock in the fix as an E2E test.

Instructions

Generate a Playwright regression test from a classified report using your project LLM key, then open a draft GitHub PR with the spec. Requires the inventory_v2 plan plus GitHub and LLM keys configured. Returns { prUrl, prNumber, branch, path }. Write; consumes LLM budget; NOT idempotent — each call opens a new PR. Use to lock in a regression as an E2E test; use generate_tdd_from_story to build a test from a mapped user story instead.

Input Schema

NameRequiredDescriptionDefault
reportIdYesReport UUID to turn into a Playwright PR (`report_id` is accepted too.)
projectIdNoProject UUID — defaults to configured project (`project_id` is accepted too.)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.1.12
    • changedInput schema / properties / projectId / description
      Previous value: -"Project UUID — defaults to configured project"New value: +"Project UUID — defaults to configured project (`project_id` is accepted too.)"
    • changedInput schema / properties / reportId / description
      Previous value: -"Report UUID to turn into a Playwright PR"New value: +"Report UUID to turn into a Playwright PR (`report_id` is accepted too.)"
  2. Changed1 schema field changedv0.1.10
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  3. First observedv0.1.0

TDQS

A4.7/5.0
Behavior5/5

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

Annotations declare the write/openWorld/non-idempotent profile, and the description reinforces it with concrete consequences: each call consumes LLM budget and opens a NEW PR, so it is explicitly non-idempotent in effect. It also discloses the credential requirement and the return shape, which matters because no output schema exists.

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?

Three dense sentences, front-loaded with the action and side effect, then preconditions and return shape, then the routing rule. No filler or restatement of the name.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers everything an agent needs for a non-idempotent, credentialed, side-effecting tool: prerequisites, budget cost, irreversibility per call, return payload, and the alternative tool. Nothing material is missing despite the absence of an output schema.

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 both parameters (reportId, projectId) and their alias forms are already documented. The description only implies that a 'classified report' and a configured project are involved, adding no format or constraint detail beyond the schema; baseline 3 applies.

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?

Names a specific verb and resource chain: generate a Playwright regression test from a classified report, then open a draft GitHub PR with the spec. It also explicitly contrasts itself with generate_tdd_from_story, so an agent can discriminate it from siblings without reading schemas.

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?

States when to use it ('lock in a regression as an E2E test') and names the alternative with its selecting condition ('use generate_tdd_from_story to build a test from a mapped user story instead'). Preconditions (inventory_v2 plan, GitHub and LLM keys) are stated up front.

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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