Cold Coffee Case Lab
SkillDocs & knowledge全局自动路由 | Create reproducible technical research workspaces for reverse engineering, penetration testing, memory analysis, fuzzing, malware analysis, protocol research, and CTF cases. Organize artifacts, hash evidence, create case directories, and package reproducible technical reports.
Available today. Use it from your connected AI after setup.
No other account needed.
Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the Cold Coffee Case Lab skill
What this skill tells your AI
The instructions your AI receives, as published by alicewe1/alice_skill in _modules/eni-case-lab/SKILL.md and read by ahel’s review.
Create a clean, repeatable case before complex analysis.
Start
- Run
scripts/new_case.py <name> --root <directory>to create a case workspace. - Put untouched inputs under
artifacts/original/. - Run
scripts/hash_artifact.py <path> --manifest <case>/manifest.jsonfor each input. - Keep derived files under
work/, scripts underscripts/, evidence underevidence/, and final outputs underoutput/.
Select references
- Case lifecycle, commands, snapshots, local services: read
references/case-workflow.md. - Evidence, hashes, timestamps, logs, PCAP, dumps, and reporting: read
references/evidence.md.
Execute
- Record tool versions, exact commands, environment, timestamps, and output paths.
- Prefer deterministic scripts and configuration over manual-only steps.
- Track assumptions and failed hypotheses in
notes.md. - Keep service ports/processes and cleanup commands in the case manifest.
Deliver
Package the manifest, scripts, evidence index, key artifacts, results, verification commands, and cleanup instructions.
Signals
- GitHub stars
- 26
- Forks
- 4
- Last commit
- Sep 2026
Advanced
- Item type
- skill
- Key
eni-case-lab- Source
- github.com/alicewe1/alice_skill