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.
npx agentmods add skills/0xranx/agentbrief/regression-testingnpx skills add 0xranx/agentbrief --skill regression-testinggit clone --depth 1 https://github.com/0xranx/agentbriefWhat 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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00057 | $0.00674 |
| Opus 5 | $0.00028 | $0.00337 |
| Sonnet 5 | $0.00011 | $0.00135 |
| Haiku 4.5 | $0.00006 | $0.00067 |
Grade A, and why
regression-testing 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.
How it starts
The opening of the file, as written. The whole thing — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Regression Testing
You are writing tests specifically to prevent regressions — bugs that were fixed but could come back.
Process
1. Identify Regression Risks
High-risk areas for regressions:
- Code that was recently fixed (the fix might be incomplete)
- Code that's frequently modified (high churn = high risk)
- Code with complex conditional logic (many branches = many ways to break)
- Code at integration boundaries (where two systems meet)
- Code without any existing tests
2. Write Characterization Tests
Before changing any code, capture current behavior:
// Characterization test: documents current behavior
// If this test breaks during refactoring, you changed behavior (intentionally or not)
it('should return empty array when no items match filter', () => {
const result = filterItems([], { status: 'active' });
expect(result).toEqual([]);
});
3. Write Regression Tests for Fixed Bugs
Every bug fix needs a regression test:
// Regression: https://github.com/org/repo/issues/123
// Bug: Processing failed when input contained unicode emoji
it('should handle unicode emoji in input', () => {
const result = processInput('Hello 👋 World');
expect(result.text).toBe('Hello 👋 World');
});
Rules for regression tests:
- Reference the original issue/bug in a comment
- Test the exact scenario that triggered the bug
- Test close variants (if emoji broke it, test other unicode too)
- Place near related tests, not in a separate "regression" file
4. Coverage-Guided Test Writing
Find untested code paths:
# Generate coverage report
pnpm test --coverage
# Look for:
# - Uncovered branches (if/else paths never hit)
# - Uncovered functions (dead code or missing tests?)
# - Low-coverage files (< 60% line coverage)
Prioritize coverage for:
- Public API functions (users depend on these)
- Error handling paths (failures should be predictable)
- Edge cases in business logic
- Data validation and transformation
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.
- 3d ago First seen · 96 lines · 57 tokens per session scan A 41cf681df327
regression-testing is a skill published in the GitHub repository 0xranx/agentbrief (45 stars, last pushed 5mo ago), licensed MIT. It adds 57 tokens to every session and 674 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 2026-08-30.
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