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.

Use Cold Coffee Case Lab in Claude, ChatGPT or Ahel Desktop

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Details

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

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Cold Coffee Case LabStart free

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

  1. Run scripts/new_case.py <name> --root <directory> to create a case workspace.
  2. Put untouched inputs under artifacts/original/.
  3. Run scripts/hash_artifact.py <path> --manifest <case>/manifest.json for each input.
  4. Keep derived files under work/, scripts under scripts/, evidence under evidence/, and final outputs under output/.

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
36
Forks
6
Last commit
Sep 2026
Advanced
Item type
skill
Key
eni-case-lab
Source
github.com/alicewe1/alice_skill