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analyzing-prefetch-files-for-execution-history

Parse Windows Prefetch files to determine program execution history including run counts, timestamps, and referenced files for forensic investigation.

50

Quality

55%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./skills/analyzing-prefetch-files-for-execution-history/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

27%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

This skill provides a comprehensive but overly verbose guide to Prefetch analysis. Its main strengths are the logical workflow sequence and concrete commands/code, but it suffers from excessive length, redundant explanatory content that Claude doesn't need, lack of validation checkpoints critical for forensic work, and a monolithic structure with no progressive disclosure. The Python parser code is also fragile and incomplete for production use.

Suggestions

Reduce content by 50%+: remove the Key Concepts table, Tools table, and Common Scenarios prose — Claude already knows these concepts and can infer tool purposes from context.

Add explicit validation checkpoints: verify file count after extraction, validate SCCA signatures before parsing, confirm hash integrity, and check for parsing errors before proceeding to analysis.

Split into multiple files: keep SKILL.md as a concise overview with the core workflow, move the Python parser to a separate script file, and put the grep patterns for suspicious tools into a reference file.

Fix the Python parser or remove it: the current code has hardcoded offsets that won't work across all versions and silently skips Win10 compressed files — either make it robust or just recommend PECmd exclusively.

DimensionReasoningScore

Conciseness

The skill is extremely verbose at ~250+ lines. It explains concepts Claude already knows (what Prefetch is, what SCCA signature means, what MAM compression is), includes lengthy reference tables, and provides extensive scenario descriptions that are largely redundant. The Key Concepts and Tools tables add significant token cost for information Claude can infer or already knows.

1 / 3

Actionability

The skill provides concrete commands and Python code, but the Python parser is incomplete/fragile (hardcoded offsets that vary by version, missing decompression for Win10 format, untested edge cases). The code is semi-executable but would likely fail on real prefetch files without modification. PECmd commands are concrete but platform-dependent assumptions are unclear.

2 / 3

Workflow Clarity

The 5-step workflow is clearly sequenced and logically ordered (extract → parse → analyze → identify suspicious → timeline). However, there are no validation checkpoints — no step verifies that prefetch files were correctly extracted, that parsing succeeded without errors, or that the integrity hashes match. For forensic operations where evidence integrity is critical, the lack of verification steps is a significant gap.

2 / 3

Progressive Disclosure

The entire skill is a monolithic wall of content with no references to external files and no bundle files to support it. The Key Concepts table, Tools table, Common Scenarios section, and detailed Output Format could all be split into separate reference files. Everything is inline, making this a very long single document with no progressive disclosure structure.

1 / 3

Total

6

/

12

Passed

Description

82%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

This is a strong, specific description that clearly identifies a niche forensic analysis capability with excellent domain-specific trigger terms. Its main weakness is the absence of an explicit 'Use when...' clause, which would help Claude know exactly when to select this skill. The specificity and distinctiveness are excellent for a forensic tooling skill.

Suggestions

Add a 'Use when...' clause such as 'Use when the user asks about Windows Prefetch analysis, .pf files, program execution artifacts, or digital forensics involving application run history.'

DimensionReasoningScore

Specificity

Lists multiple specific concrete actions: 'Parse Windows Prefetch files', 'determine program execution history', 'run counts', 'timestamps', 'referenced files', and 'forensic investigation'. These are all concrete, specific capabilities.

3 / 3

Completeness

Clearly answers 'what does this do' (parse Prefetch files to determine execution history with specific data points), but lacks an explicit 'Use when...' clause or equivalent trigger guidance, which caps this at 2 per the rubric.

2 / 3

Trigger Term Quality

Includes strong natural keywords a forensic analyst would use: 'Windows Prefetch files', 'program execution history', 'run counts', 'timestamps', 'referenced files', 'forensic investigation'. These are the exact terms someone working in digital forensics would naturally use.

3 / 3

Distinctiveness Conflict Risk

Highly distinctive niche: Windows Prefetch file parsing for forensic investigation is a very specific domain unlikely to conflict with other skills. The combination of 'Prefetch files', 'forensic investigation', and specific artifact types makes this clearly distinguishable.

3 / 3

Total

11

/

12

Passed

Validation

90%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation10 / 11 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

10

/

11

Passed

Repository
mukul975/Anthropic-Cybersecurity-Skills
Reviewed

Table of Contents

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