SKILLEMALL.ai
GitHub ↗ RU Sign in

CC performing-windows-artifact-analysis-with-eric-zimmerman-tools

Performs comprehensive Windows forensic artifact analysis using Eric Zimmerman's open-source EZ Tools suite (KAPE, MFTECmd, PECmd, LECmd, JLECmd, Timeline Explorer) to parse registry hives, prefetch files, event logs, and file system metadata. Use during DFIR investigations that need a timeline of program execution, file access, and persistence built from Windows artifacts.

mukul975/Anthropic-Cybersecurity-Skills Agent Skills author: mukul975 Apache-2.0 8 files · 2 scripts body ≈ 2 804 tokens Open the sourcegithub.com↗ analyzed 5 d ago

Performs comprehensive Windows forensic artifact analysis using Eric Zimmerman's open-source EZ Tools suite (KAPE, MFTECmd, PECmd, LECmd, JLECmd, Timeline…

As a process C 62/100 · Has gaps — weak spots: when it triggers, failures and branches, running it twice

AnalyzerInfrastructureData and analyticsPersonal productivitytype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
C
87/100
safety, quality, tests
Safety 60%
95
Quality 40%
74
Run on models
none yet
Process rating
C
62/100
Has gaps
Failures and branches w 10
0
When it triggers w 12
20
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 5

    ✓ No critical or high findings

    Medium and low: 5
    • low Risky intent intent-offensive-security assets/template.md:47
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      ### Lateral Movement Indicators
    • low Risky intent intent-offensive-security references/standards.md:53
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      - T1021 - Remote Services: Lateral movement via event log analysis
    • low Risky intent intent-offensive-security references/workflows.md:59
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      ## Workflow 4: Lateral Movement Investigation
    • low Risky intent intent-offensive-security references/workflows.md:77
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      Step 6: Map lateral movement path across systems
    • low Risky intent intent-offensive-security SKILL.md:275
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      ### Lateral Movement Detection

    Files scanned: 8. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "domain"
    • note frontmatter-key unknown frontmatter key "subdomain"
    • note frontmatter-key unknown frontmatter key "nist_csf"
    • note frontmatter-key unknown frontmatter key "mitre_attack"

    Process rating: all ten parameters 62/100

    • 0Failures and branches. Linear process with no failure handling
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 4 mutating operations with no state check
    • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 42 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2804 tokens
    • 100Progress reporting. Reports progress

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • -4Absolute local paths (C:\Users, /home/…): not portable
    • -43 reference files, but SKILL.md never points to them: the model will not open them
    • -32 of 2 scripts are never mentioned in SKILL.md
    • +2Single-language instructions
    • +3Description length 376: enough signal without eating the budget
    • +4Structure: 25 headings
    • +3Step-by-step instructions: 42 items
    • +3Output format is stated explicitly
    • +4Has examples (12 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.