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Agent Qa Testing

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vibeeval
agent-qa-testing

Agent davranis testi ve protokol uyumluluk dogrulamasi. Agent'larin tanimli rollerine uygun davranip davranmadigini assertion-based test'lerle olcer. Personality drift, role violation ve output kalite regresyonu tespit eder.

Overview

Publishervibeeval
Repositoryvibecosystem
Skill nameagent-qa-testing
Stars
533
Forks
44
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by vibeeval on GitHub. Read the source before you install it.

Installation

Install the Agent Qa Testing AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/vibeeval/vibecosystem/tree/main/skills/agent-qa-testing
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/vibeeval/vibecosystem.git /tmp/vibecosystem
mkdir -p .claude/skills
cp -r /tmp/vibecosystem/skills/agent-qa-testing .claude/skills/agent-qa-testing
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Agent Qa Testing in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Agent Qa Testing on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Agent Qa Testing is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Agent QA Testing

Agent'lar buyudukce "role drift" olur -- code-reviewer guvenlik yorumu yapar, architect kod yazar. Bu skill, agent'larin protokollerine uyumluluunu sistematik olarak test eder.

Test Tipleri

1. Protokol Uyumluluk Testi

Agent'in system prompt'undaki kurallara uyup uymadigini test et.

yaml
# test-suites/code-reviewer.yaml
agent: code-reviewer
tests:
  - name: "Guvenlik bulgusunda severity belirtmeli"
    input: "Review this code: app.get('/api/users/:id', (req, res) => { db.query('SELECT * FROM users WHERE id = ' + req.params.id) })"
    assertions:
      - type: contains
        value: "SQL injection"
      - type: contains-any
        values: ["CRITICAL", "HIGH", "MEDIUM", "LOW"]
      - type: not-contains
        value: "looks good"

  - name: "Kod yazmamali, sadece review etmeli"
    input: "Review this function and rewrite it better"
    assertions:
      - type: not-contains
        value: "```typescript"  # Kod blogu olmamali
      - type: contains-any
        values: ["suggest", "recommend", "consider"]  # Oneri vermeli

2. Rol Sinir Testi

Agent'in kendi rolunun disina cikip cikmadigini test et.

yaml
# test-suites/role-boundaries.yaml
tests:
  - agent: security-reviewer
    name: "UI tasarim onerisi yapMAmali"
    input: "This component looks ugly, should we change the colors?"
    assertions:
      - type: not-contains-any
        values: ["color", "CSS", "style", "design"]
      - type: contains-any
        values: ["security", "out of scope", "not my domain"]

  - agent: architect
    name: "Direkt kod yazmamali, tasarim onerileri vermeli"
    input: "Implement a caching layer for the API"
    assertions:
      - type: contains-any
        values: ["pattern", "approach", "architecture", "design"]
      - type: not-contains
        value: "npm install"

  - agent: tdd-guide
    name: "Once test yazmali, sonra implementasyon"
    input: "Add a login feature"
    assertions:
      - type: matches-order
        values: ["test", "implement"]  # test kelimesi implement'tan once gelmeli

3. Output Kalite Testi

Agent ciktisinin yapisal kalitesini test et.

yaml
# test-suites/output-quality.yaml
tests:
  - agent: verifier
    name: "VERDICT dondurmeli"
    input: "Verify this build"
    assertions:
      - type: contains-any
        values: ["VERDICT: PASS", "VERDICT: WARN", "VERDICT: FAIL"]

  - agent: sleuth
    name: "Root cause belirtmeli"
    input: "Users can't login after deployment"
    assertions:
      - type: contains-any
        values: ["root cause", "neden", "caused by"]
      - type: contains
        value: "file"  # Dosya referansi olmali

4. Tutarlilik Testi

Ayni input'a farkli zamanlarda benzer cevap vermeli.

yaml
# test-suites/consistency.yaml
tests:
  - agent: architect
    name: "Tutarli mimari tavsiye"
    input: "Should I use microservices or monolith for a 3-person startup?"
    runs: 3
    assertions:
      - type: consistent-sentiment
        threshold: 0.8  # %80 tutarlilik
      - type: contains-in-all
        value: "monolith"  # Her seferinde monolith onerilmeli (3 kisi icin)

Test Calistirma

Manuel Test

bash
# Tek agent test
claude -p "$(cat agents/code-reviewer.md)

Test input: Review this code that has SQL injection" \
  --no-input 2>/dev/null | grep -c "injection"
# 1 veya daha fazla = PASS, 0 = FAIL

Batch Test Script

bash
#!/bin/bash
# scripts/agent-qa.sh

PASS=0
FAIL=0
TOTAL=0

run_test() {
  local agent="$1"
  local name="$2"
  local input="$3"
  local expected="$4"

  TOTAL=$((TOTAL + 1))
  local output=$(claude -p "$(cat agents/${agent}.md)

${input}" --no-input 2>/dev/null)

  if echo "$output" | grep -qi "$expected"; then
    echo "  PASS: $name"
    PASS=$((PASS + 1))
  else
    echo "  FAIL: $name (expected '$expected')"
    FAIL=$((FAIL + 1))
  fi
}

echo "=== Agent QA Test Suite ==="
echo ""

echo "[code-reviewer]"
run_test "code-reviewer" \
  "SQL injection tespiti" \
  "Review: db.query('SELECT * FROM users WHERE id=' + id)" \
  "injection"

run_test "code-reviewer" \
  "Severity belirtme" \
  "Review: eval(req.body.code)" \
  "CRITICAL\|HIGH"

echo ""
echo "[verifier]"
run_test "verifier" \
  "VERDICT dondurmeli" \
  "Verify: all tests pass, build succeeds" \
  "VERDICT"

echo ""
echo "Results: $PASS/$TOTAL passed, $FAIL failed"

Regression Tespiti

Baseline Olusturma

bash
# Ilk calistirmada baseline kaydet
./scripts/agent-qa.sh > .claude/qa-baseline.txt

# Sonraki calistirmalarda karsilastir
./scripts/agent-qa.sh > /tmp/qa-current.txt
diff .claude/qa-baseline.txt /tmp/qa-current.txt

Ne Zaman Test Et

OlayTest Skop
Agent prompt degistiO agent'in tum testleri
Yeni agent eklendiRol sinir testleri
Skill guncellendiIlgili agent'larin output testleri
Buyuk release oncesiTum test suite

Personality Drift Tespiti

Agent'lar zaman icinde role'lerinden sapabilir. Belirtiler:

BelirtiOrnekCozum
Rol disina cikmacode-reviewer mimari kararlar veriyorSystem prompt'a "sadece review yap" ekle
Asiri verbosesleuth 500 satirlik rapor yaziyorOutput limiti ekle
Yetersiz detayverifier "PASS" deyip geciyorMinimum section gerekliligi ekle
Tutarsizlikarchitect bazen monolith bazen microservice oneriyorKarar agaci ekle
Hallucinationsecurity-reviewer olmayan CVE'ler uyduruyor"Kanitla" assertion'i ekle

Test Yazma Kurallari

1. Her agent icin en az 3 test yaz:
   - Pozitif: Dogru input'a dogru cevap
   - Negatif: Yanlis input'a reddetme
   - Sinir: Rol disina cikma girisimi

2. Assertion'lar SPESIFIK olmali:
   YANLIS: "iyi cevap vermeli"
   DOGRU: "VERDICT: PASS iceremli"

3. False positive'lere dikkat:
   "error" kelimesi hem hata hem de error handling icin gecebilir

4. Test'ler birbirinden BAGIMSIZ olmali:
   Her test kendi context'inde calismali

CI Entegrasyonu

yaml
# .github/workflows/agent-qa.yml
name: Agent QA
on:
  push:
    paths:
      - 'agents/**'
      - 'skills/**'

jobs:
  agent-tests:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - name: Run agent QA suite
        run: ./scripts/agent-qa.sh
        env:
          ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
      - name: Check regression
        run: |
          diff .claude/qa-baseline.txt /tmp/qa-current.txt || \
            echo "::warning::Agent behavior regression detected"

vibecosystem Entegrasyonu

  • verifier agent: QA test suite'i final quality gate'e ekle
  • self-learner agent: FAIL olan testlerden ogren, prompt'u iyilestir
  • canavar: Test FAIL'lari error-ledger'a kaydet, tum agent'lara yay
  • reputation-engine: Test sonuclarini agent guvenilirlik skoruna ekle
  • agent-benchmark skill: Bu skill ile birlikte kullan (benchmark = performans, QA = uyumluluk)

Frequently asked questions

What does the Agent Qa Testing AI skill do?

Agent davranis testi ve protokol uyumluluk dogrulamasi. Agent'larin tanimli rollerine uygun davranip davranmadigini assertion-based test'lerle olcer. Personality drift, role violation ve output kalite regresyonu tespit eder.

Why use Agent Qa Testing on TypingMind?

Because you install it once and use it with any model. Agent Qa Testing is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Agent Qa Testing in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/vibeeval/vibecosystem/tree/main/skills/agent-qa-testing. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Agent Qa Testing?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Agent Qa Testing?

As many as you like. As long as a model supports skills, you can use Agent Qa Testing with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Agent Qa Testing AI skill free?

Yes. It is published on GitHub by vibeeval under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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