Works with the AI tools you already use
Claude Code
Cursor
Codex CLI
Muse
Dots+22 moreClaude CodeCursorCodex CLIMuseDots
OpenClaw
Manus
Grok
Grok Bot+18 agentsagent incident to regression builder
Turn redacted agent incident traces into reproducible regression tests and score candidate fixes.
$15
agent incident to regression builder
Example session with this skill installed
Process this redacted incident trace from a failed refund agent and generate regression assertions. Compare it against the candidate fix trace in candidate_01.json.
- Read your context and instructions
- Compiled the agent incident to
I have processed the incident trace and evaluated the candidate fix. The original failure was rooted in a sequence violation where the refund was initiated before the return shipping label was generated.
Regression Analysis and Assertion Scoring
| Assertion ID | Description | Incident Status | Candidate Status | Stability ID |
|---|---|---|---|---|
| ARG-001 | Order status must be 'Returned' before refund_execute | FAIL | PASS | UUID-8821 |
| ARG-002 | generate_label must precede refund_execute | FAIL | PASS | UUID-8822 |
| ARG-003 | Stable customer pseudonym consistent across trace | PASS | PASS | USER-ALT-09 |
| ARG-004 | Tool notify_customer contains refund amount | FAIL | PASS | MSG-992 |
Implementation Evidence
{
"fixture_version": "1.0.4",
"source_provenance": "incident-trace-2024-05-12.json",
"assertions": [
{
"id": "ARG-002",
"type": "causal_order",
"predecessor": "tool_call:generate_label",
"successor": "tool_call:refund_execute"
}
],
"coverage_gap_report": "No assertion currently validates if the refund amount matches the original transaction ID in the ledger."
}
Next steps
- Integrate the generated JSON fixture into the
tests/regression/agents/directory. - Run
scripts/replay.py --verify-fixto confirm the candidate trace passes in the CI environment. - Review the identified coverage gap regarding ledger amount validation and update the behavior oracle.
Connects securely to your tools. The creator never sees your data.
What you get
About this skill
The problem
Translating a messy agent failure into a reproducible regression test is manual and error-prone. Raw traces often contain sensitive data or transient state that prevents them from being used as stable test fixtures.
What it does
- Transforms redacted agent traces and behavioral oracles into formal regression assertions.
- Validates that original incident logs correctly trigger assertion failures.
- Scores candidate traces against existing assertion sets to verify fixes.
- Preserves causal event ordering while maintaining stable pseudonymous IDs for testing.
- Identifies coverage gaps where existing assertions fail to capture observed behaviors.
Frameworks & tools
Python (scripts/replay.py), JSON-based trace formats, and custom sandbox adapters.
Why this beats prompting it yourself
General LLMs often hallucinate missing data or ignore strict causal order when interpreting logs. This skill enforces evidence discipline, ensuring reports distinguish between supplied observations and live test results without leaking credentials.
Use cases
- Converting a production agent crash into a permanent CI regression test.
- Verifying if a model update fixes a specific multi-step logic error.
- Auditing agent traces for behavioral compliance against a reviewed oracle.
- Generating synthetic test fixtures from redacted customer support incidents.
Known limitations
Does not execute live tool commands. Requires pre-recorded traces and reviewed oracles. Coverage is limited to trace analysis and does not constitute a full system audit.
How to install
Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.
- 1
Download the ZIP
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- 2
Unzip into your skills folder
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- 3
Ask your agent to use it
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Needs access to
Json Schema