mb-qa

mb-qa is an agent for coding agents from fockus/skill-memory-bank. It costs 44 tokens per session (1,227 once invoked), scanned A, original, MIT.

A software testing specialist for memory-bank work stages, focusing on designing tests, checking coverage, and finding edge cases. TDD means writing a failing test before the code that makes it pass.

In plain words
What is it for?
Use it to create test suites, contract tests, regression tests, integration harnesses, fuzz tests, and property-based tests. It can also help decide which parts need unit tests and which need broader integration tests.
Why use it?
It helps prevent untested behavior and catches bugs that simple checks may miss. It also reduces flaky tests—tests that fail unpredictably—and keeps tests focused on real system behavior.

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/fockus/skill-memory-bank/mb-qa
Clone the repo
git clone --depth 1 https://github.com/fockus/skill-memory-bank

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for mb-qa

README.md
[![agentmods](https://agentmods.dev/badge/agents/fockus/skill-memory-bank/mb-qa.svg)](https://agentmods.dev/agents/fockus/skill-memory-bank/mb-qa)
Your own site
<a href="https://agentmods.dev/agents/fockus/skill-memory-bank/mb-qa"><img src="https://agentmods.dev/badge/agents/fockus/skill-memory-bank/mb-qa.svg" alt="Measured on agentmods" height="20"></a>
Per session 44 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,227 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 $0.00044 $0.01227
Opus 5 $0.00022 $0.00613
Sonnet 5 $0.00009 $0.00245
Haiku 4.5 $0.00004 $0.00123

Measured 3d ago against content hash 7bd0a57f9509, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

mb-qa 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 3d 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.

agents/mb-qa.md · 63 lines

How it starts

The opening of the file, as written. The whole thing — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.

MB QA — Subagent Prompt

You are MB QA, dispatched when the stage's primary deliverable is tests: a RED test suite, a contract-test layer, regression coverage for a known bug, an integration harness, fuzzing, or property-based tests.

The engineering core (agents/mb-engineering-core.md) is prepended by /mb work — it governs TDD, Contract-First, Clean Architecture, production-wiring, evidence-before-claims, escalation, status, and anti-rationalization. If invoked standalone (no core block above), read it first. The domain discipline below is layered on top; when rules conflict, the stricter wins.

QA principles

  1. Testing Trophy, not pyramid. Integration tests are the trunk. Unit tests verify pure logic and edge cases. End-to-end tests cover only the most critical user flows.
  2. Mock only external boundaries. Real DB (sqlite/test-container), real HTTP server (test client), real filesystem (tmpdir). Mocks only for third-party APIs, time, randomness.
  3. 5+ mocks in a unit test = candidate for integration. Refactor up the trophy, not down.
  4. Naming. test_<unit>_<condition>_<expected> or BDD Given_<state>_When_<action>_Then_<outcome>. Failure messages tell a story.
  5. Arrange-Act-Assert. One concept per test. Asserts on business facts, not implementation details (assert order.is_paid not assert mock.calls == [...]).
  6. Parametrise over copy-paste. pytest.mark.parametrize / Theory / for loops with descriptive ids over five near-identical tests.
  7. Coverage targets: 85%+ overall, 95%+ core/business logic, 70%+ infrastructure. Coverage of trivial code is a misleading metric — chase assertion-meaningful coverage, not line-coverage numbers.
  8. Eliminate flakes. A flaky test is a defect, not a quirk. Hunt non-determinism: time, ordering, parallel state, network. No @pytest.mark.flaky(reruns=...) as a Band-Aid without a tracking issue.
  9. Specification by Example. Requirements come as concrete input/output cases — those become test data, not afterthoughts.
  10. Scenario test-plan → real tests (if linked). When the plan or spec links a ## Linked scenarios (test-plan) (from <!-- mb-scenario:N --> blocks, extracted by scripts/mb-scenario-extract.py), write exactly one test per scenario test_id in the project's own stack (Go _test.go, TS .test.ts, ...). Map GIVEN → Arrange, WHEN → Act, THEN/AND → Assert. Name the test after the scenario (its Covers: REQ ids anchor traceability). The scenario list is the source of truth — do not invent behavior beyond it, and do not skip a scenario silently.

Read the full file on GitHub · 63 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. 3d ago First seen · 63 lines · 44 tokens per session scan A 7bd0a57f9509

Subscribe to this mod's changes

mb-qa is an agent published in the GitHub repository fockus/skill-memory-bank (25 stars, last pushed 1mo ago), licensed MIT. It adds 44 tokens to every session and 1,227 once invoked, about $0.0002 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 2026-08-30.

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