Reproduce the cause
SkillDev toolsDemonstrate a diagnosed DeepReason cause with the smallest offline artifact — a failing test or a minimal script against the committed record. Use after DIAGNOSIS.md, before any fix.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Reproduce the cause skill
What this skill tells your AI
The instructions your AI receives, as published by ahepi/deepreason in .claude/skills/dr-reproduce/SKILL.md and read by ahel’s review.
Input: DIAGNOSIS.md's falsifiable prediction. Output: REPRO.md plus one runnable artifact that shows the defect NOW (and will show its absence after the fix). You still change no production code.
Choose the cheapest sufficient form, in this order
- Record replay — the defect is already capted in a committed run
root: a script that runs
verify_root(<root>)or walks the log and prints the violating fact. Zero live cost; deterministic. - Offline unit reproduction — construct the minimal state in a
test: register the same problems/artifacts/policies the record
shows and assert the wrong behavior happens. Reuse existing test
helpers (
_prepare_run, controller fixtures,_policybuilders) from the nearesttests/test_*.py; do not invent new scaffolding when a helper exists. - Minimal in-memory check — a 20-line python3 heredoc proving the
mechanism (e.g. round-trip a receipt through
canonical_jsonand show key order changes). Acceptable as evidence, but pair it with form 1 or 2 for the regression artifact.
NEVER reproduce by launching a live provider run. Live runs are for
dr-verify-outcome, at most once, and only if the goal demands it.
Fidelity rules
- The reproduction must mirror the live conditions the record shows, not a convenient simplification. If admission auto-accepted import-role artifacts before cycle 0, your fixture registers those artifacts too. A reproduction that passes for a different reason than the live failure will approve a wrong fix.
- One assertion states the DEFECT (currently failing or currently printing the violation), phrased so it inverts cleanly post-fix.
- Respect frozen-record invariants in fixtures: one manifest sha per capability chain, constant fence seqs within a proposal's chain — fixture WellFormednessError means your fixture is wrong, not the harness.
REPRO.md template
# Reproduction
Form: record-replay | unit-test | in-memory
Artifact: <path (test id) or inline command>
Current output: <paste the failing/violating output, trimmed>
Confirms diagnosis: yes — <one line linking output to mechanism>
Post-fix expectation: <exact output/assertion after a correct fix>
If the reproduction REFUTES the diagnosis: write that in REPRO.md,
commit, and return to the orchestrator routing back to dr-diagnose.
A refuted diagnosis is a successful phase, not a failure.
Exit criteria
- REPRO.md + artifact committed and pushed.
- The artifact demonstrably shows the defect today (output pasted).
- Production code untouched.
- Return to the orchestrator.
Signals
- GitHub stars
- 142
- Forks
- 14
- Last commit
- Sep 2026
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dr-reproduce- Source
- github.com/ahepi/deepreason