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regression-test

Manage golden dataset regression tests for LLM prompts using Promptfoo. Commands — init, add, run, report. Use when user says "regression", "golden dataset", "prompt regression", "eval run", "test my prompts", or after shipping prompt changes.

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SKILL.md (original)

Review the instructions the agent will receive before you install.

Regression Test: Golden Dataset Management

Manage golden test datasets for LLM prompt regression testing using Promptfoo. Ensures prompt changes don't degrade output quality.

One eval tells you today's score. A kept set tells you what your change did. There is a recorded three-run walkthrough of exactly that, runnable with no API key, at https://github.com/7alexhale5-rgb/alexhale-skills/tree/main/example

Prerequisite: npm install -g promptfoo (check with which promptfoo)


Commands

/regression-test init

Scaffold regression testing infrastructure in the current project.

  1. Create directory structure:

    mkdir -p .promptfoo/golden
    
  2. Generate .promptfoo/promptfooconfig.yaml (the path matters: tests: "golden/*.yaml" below resolves relative to this file, and /regression-test run looks for it here):

    description: "Golden dataset regression tests"
    # Without this, promptfoo has no prompt to send and every case scores an empty string.
    # The vars come from the golden files that `/regression-test add` writes.
    prompts:
      - |
        [{"role":"system","content":"{{system_prompt}}"},{"role":"user","content":"{{user_input}}"}]
    providers:
      - id: anthropic:messages:claude-sonnet-5
        config:
          temperature: 0
    tests: "golden/*.yaml"
    defaultTest:
      assert:
        - type: llm-rubric
          value: "Output should match the expected behavior described in the test case"
    
  3. Add .promptfoo/results/ to .gitignore if not already present. Ignore the results, commit the goldens: a golden dataset nobody else can see is not a shared baseline, and the whole point is that your teammates and your CI run the same cases you do. If a prompt in a golden case is genuinely sensitive, keep that one case out of the repo rather than hiding the dataset.

  4. Report: "Initialized .promptfoo/golden/ — run /regression-test add <name> to capture test cases."


/regression-test add <name>

Capture a prompt+response pair as a golden test case.

  1. Parse <name> from user input (slug format, e.g., auth-flow, error-handling)

  2. Prompt user for:

    • System prompt (or detect from current project's CLAUDE.md/skill)
    • User input (the test prompt)
    • Expected behavior (natural language description of good output)
    • Vars (optional template variables)
  3. Write golden test case:

    # .promptfoo/golden/{name}.yaml
    - description: "{name}"
      vars:
        system_prompt: |
          {system prompt content}
        user_input: |
          {user input}
      assert:
        - type: llm-rubric
          value: |
            {expected behavior description}
        - type: not-contains
          value: "error"
    
  4. Report: "Added golden test {name} — {N} total test cases."


/regression-test run

Execute Promptfoo evaluation against all golden datasets.

  1. Check prerequisites:

    which promptfoo 2>&1  # must return path
    ls .promptfoo/golden/*.yaml 2>/dev/null | wc -l  # must be > 0
    
  2. Run evaluation:

    cd {project_root}
    promptfoo eval --config .promptfoo/promptfooconfig.yaml \
      --output .promptfoo/results/eval-$(date +%Y%m%d-%H%M%S).json \
      --no-cache 2>&1
    
  3. Parse results JSON:

    • Count PASS/FAIL per test case
    • Extract failure details (expected vs actual)
  4. Report:

    Regression Test Results
    ├─ Total: {N} test cases
    ├─ Pass: {N} ({%})
    ├─ Fail: {N} ({%})
    └─ Duration: {N}s
    
    Failures:
    - {test_name}: {assertion_type} — expected "{expected}", got "{actual}"
    
  5. If all pass: "All golden tests pass — safe to ship." If failures: "Regressions detected — review before shipping."


/regression-test report

Show regression trends over the last 5 evaluations.

  1. Read result files:

    ls -t .promptfoo/results/eval-*.json | head -5
    
  2. For each result file, extract:

    • Date (from filename)
    • Pass/fail counts
    • Any new failures vs previous run
  3. Report:

    Regression Trends (last 5 evals)
    ├─ 2026-03-31 14:30: 12/12 PASS ✓
    ├─ 2026-03-30 09:15: 11/12 PASS (1 fail: auth-flow)
    ├─ 2026-03-29 16:45: 12/12 PASS ✓
    ├─ 2026-03-28 11:00: 10/12 PASS (2 fail)
    └─ 2026-03-27 08:30: 12/12 PASS ✓
    
    Trend: STABLE (4/5 clean)
    

Where to wire it in

The value shows up when the run is automatic, not when you remember to type it.

MomentWhat to do
After changing any prompt/regression-test run before you commit. This is the one that catches most regressions.
Before a releaseRun it in CI and fail the build on a new failure. promptfoo eval returns non-zero when an assertion fails.
After a model or version changeRe-run the whole set. A provider upgrade is a silent prompt change.
Weekly, on a schedule/regression-test report to see whether quality is drifting rather than breaking.

If your agent harness supports hooks or a pre-commit step, put the run there. A check that depends on discipline is a check you will lose.


Graceful Degradation

ComponentIf MissingFallback
promptfoo CLINot installedPrompt user: npm install -g promptfoo
.promptfoo/ directoryNot initializedPrompt: /regression-test init
Golden datasetsNo .yaml filesSkip with note: "No golden tests — add with /regression-test add"
Results directoryMissingCreate on first run

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