analyzing-windows-lnk-files-for-artifacts
Parse Windows LNK shortcut files to extract target paths, timestamps, volume information, and machine identifiers for forensic timeline reconstruction.
69
62%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./skills/analyzing-windows-lnk-files-for-artifacts/SKILL.mdQuality
Discovery
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 narrow forensic analysis domain with concrete actions and excellent trigger terms. Its main weakness is the absence of an explicit 'Use when...' clause, which would help Claude know precisely when to select this skill. Adding that clause would make this description excellent.
Suggestions
Add an explicit 'Use when...' clause, e.g., 'Use when the user asks about analyzing Windows shortcut (.lnk) files, forensic artifact extraction, or timeline reconstruction from LNK metadata.'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: parse LNK files, extract target paths, timestamps, volume information, machine identifiers, and forensic timeline reconstruction. | 3 / 3 |
Completeness | Clearly answers 'what does this do' (parse LNK files, extract various metadata for forensic timeline reconstruction), but lacks an explicit 'Use when...' clause specifying when Claude should select this skill. | 2 / 3 |
Trigger Term Quality | Includes strong natural keywords a forensic analyst would use: 'Windows LNK', 'shortcut files', 'target paths', 'timestamps', 'volume information', 'machine identifiers', 'forensic timeline reconstruction'. These are terms users in this domain would naturally mention. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive niche targeting Windows LNK shortcut file forensics specifically. Very unlikely to conflict with other skills given the narrow domain of LNK file parsing and forensic analysis. | 3 / 3 |
Total | 11 / 12 Passed |
Implementation
42%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The skill excels at actionability with complete, executable code for LNK file forensic analysis, but suffers significantly from verbosity and poor content organization. It explains concepts Claude already knows, provides redundant tool descriptions, includes lengthy narrative scenarios without actionable steps, and packs everything into a single monolithic file. The workflow lacks validation checkpoints critical for forensic evidence handling.
Suggestions
Remove the Key Concepts and Tools & Systems tables entirely or move them to a separate REFERENCE.md file — Claude already knows what LNK files and Jump Lists are.
Convert the Common Scenarios section from narrative descriptions into actionable checklists with specific commands, or move them to a separate SCENARIOS.md file.
Add explicit validation checkpoints: hash verification after LNK collection, row count verification after CSV generation, and integrity checks before analysis steps.
Choose either LECmd or Python as the primary approach and move the alternative to a separate file to reduce inline content by ~40%.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is extremely verbose at ~250+ lines. It includes extensive prerequisite lists, a large key concepts table explaining things Claude already knows (what a .lnk file is, what Jump Lists are), a full tools table with obvious descriptions, four detailed scenario descriptions that are purely narrative without actionable steps, and redundant approaches (LECmd AND Python parsing). Much of this could be cut in half. | 1 / 3 |
Actionability | The skill provides fully executable bash commands and Python scripts that are copy-paste ready. The code includes proper imports, file I/O, CSV output, and specific field extraction. Both LECmd command-line usage and Python LnkParse3 approaches are concrete and complete. | 3 / 3 |
Workflow Clarity | The four steps are clearly sequenced (collect → parse with LECmd → parse with Python → analyze), but there are no validation checkpoints. No hash verification after collection, no validation that LNK files were properly copied, no error recovery loops. For forensic operations where evidence integrity is critical, the absence of verification steps is a significant gap. | 2 / 3 |
Progressive Disclosure | This is a monolithic wall of content with no references to external files. The Python parsing script alone is ~70 lines inline. The key concepts table, tools table, four scenario descriptions, and output format template all bloat the main file when they could be split into referenced documents. Everything is crammed into one file with no navigation structure. | 1 / 3 |
Total | 7 / 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.
Validation — 10 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 10 / 11 Passed | |
- Repository
- mukul975/Anthropic-Cybersecurity-Skills
- Commit
c15f73d
- Reviewed
Table of Contents
Is this your skill?
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.