verification

A workflow for proving that a bug exists, checking that a fix solves it, and running tests for regressions. A regression is a problem introduced when a change breaks something that previously worked.

In plain words
What is it for?
Use it to create minimal bug reproductions, validate fixes with the same checks, run project tests, and remove temporary reproduction files.
Why use it?
It replaces assumptions about a fix with fresh evidence from a reproducible failure, a passing check, and the existing test suite.

Skill for Claude CodeCodex

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 skills/dineshdb/pie/verification
Any agent
npx skills add dineshdb/pie --skill verification
Clone the repo
git clone --depth 1 https://github.com/dineshdb/pie

Made for: Claude Code, Codex.

Per session 14 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 232 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 $0.00014 $0.00232
Opus 5 $0.00007 $0.00116
Sonnet 5 $0.00003 $0.00046
Haiku 4.5 $0.00001 $0.00023

Measured 2d ago against content hash 45242201dc55, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

verification 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.

.pie/skills/verification/SKILL.md · 38 lines

What it actually says

Verification Workflow

Evidence-based development. No completion claims without fresh proof of success.

1. Reproduction (The "Failing State")

Before fixing, prove the bug exists with a minimal test or script.

cat > repro.py << 'EOF'
# Minimal code to trigger the failure
EOF
python3 repro.py # Should FAIL

2. Validation (The "Passing State")

After implementation, run the same reproduction script to confirm the fix.

python3 repro.py # Should now PASS

3. Regression Check

Ensure no collateral damage by running existing test suites.

cargo test
uv run pytest
repo verify

Principles

  • Repro First: Never fix a bug you haven't reproduced.
  • Isolate: Keep reproduction scripts minimal and independent.
  • Clean Up: Remove temporary repro scripts after verification is complete.
  • Evidence: Prefer actual command output over "hand-wavy" assertions of success.
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 · 38 lines · 14 tokens per session scan A 45242201dc55

Subscribe to this mod's changes

verification is a skill published in the GitHub repository dineshdb/pie (2 stars, last pushed 3mo ago), licensed MIT. It adds 14 tokens to every session and 232 once invoked, about $0.0001 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.

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