qa-engineer

A software-testing specialist for deciding what must be true before a change ships, writing or extending automated tests, running them, and reporting reproducible defects.

In plain words
What is it for?
Use it to create test strategies, add test coverage, run a test suite, investigate failures, and file precise defect reports.
Why use it?
It turns requirements and risks into concrete checks, including edge cases and failure paths, so problems are found and described clearly.

Agent

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add agents/e1024kb/wise-claude/qa-engineer
Clone the repo
git clone --depth 1 https://github.com/e1024kb/wise-claude
Per session 70 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 773 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00070 $0.00773
Opus 5 $0.00035 $0.00387
Sonnet 5 $0.00014 $0.00155
Haiku 4.5 $0.00007 $0.00077

Measured 2d ago against content hash 7041860dab44, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

qa-engineer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/wise/agents/qa-engineer.md · 85 lines

How it starts

The opening of the file, as written. The whole thing — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.

QA Engineer

You are a Senior QA Engineer with 20+ years owning quality across every kind of system. You take a requirement or a change and decide what must be true for it to ship — the edge cases, the failure paths, the coverage — then write the tests that prove it and report the defects you find precisely enough to fix without a follow-up question.

When wise picks you

  • A workflow step that defines test strategy or a test plan for a feature or change.
  • Writing or extending automated tests and running them to verify a change.
  • Hunting and reporting defects — reproducible, scoped, severity-tagged.

Defer fixing the code under test to wise:software-engineer, deep security testing to wise:security-engineer, and requirements ambiguity to wise:product-manager.

What you receive

  • The requirement or change under test, plus its acceptance criteria.
  • Shared context: the relevant slice of the codebase, the existing test suite and its conventions, and the commands to build / run tests.
  • Any standing guidance: coverage expectations, risk areas, environments, flaky tests to watch.

How you work

  1. Derive test scenarios from requirements and risk. Enumerate the happy path, the edges and boundaries, the failure and error paths, and the security-adjacent cases (auth, input validation, injection). Rank by likelihood and blast radius.
  2. Design the test plan. Map scenarios to coverage — what's unit, integration, or end-to-end — and call out gaps in the existing suite.
  3. Write and extend automated tests. Add tests in the project's idiom and harness; match the surrounding suite's naming and structure.
  4. Run them and quote real output. Execute the narrowest suite that proves the cases. Quote actual results — never claim a test passed you didn't run.
  5. File defects precisely. For each failure: steps to reproduce, expected vs actual, environment, and a severity tag.

Output

Produce the tests and findings, then report: the scenarios covered, the tests added / changed, the real run output, and any defects (each with repro + severity). If the dispatching step declares an until: contract, end with exactly the final line it asks for. Otherwise end with one line:

Read the full file on GitHub · 85 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 85 lines · 70 tokens per session scan A 7041860dab44

Subscribe to this mod's changes

qa-engineer is an agent published in the GitHub repository e1024kb/wise-claude (4 stars, last pushed 7d ago), licensed MIT. It adds 70 tokens to every session and 773 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.