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analyzing-android-malware-with-apktool

Perform static analysis of Android APK malware using apktool for resource decompilation, jadx for Java source recovery, and androguard for manifest inspection, dangerous permission-combination detection, and identification of obfuscated code, dynamic code loading, and reflection-based API calls. Use to statically triage a suspicious APK without executing it or to build mobile malware detection rules.

63

Quality

75%

Does it follow best practices?

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SecuritybySnyk

High

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tessl review fix ./skills/analyzing-android-malware-with-apktool/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

65%

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

The skill body is concise and well-structured with a clear step sequence, but it stays abstract: it gives no executable code or commands and fails to point to the bundled agent.py and api-reference.md that actually implement the described workflow. Adding invocation examples and links would lift the actionability and progressive-disclosure scores.

Suggestions

Reference the bundled tooling directly, e.g. 'Run `python scripts/agent.py sample.apk full` for the full analysis; see references/api-reference.md for per-command usage and the androguard API table'.

Add at least one executable code snippet or CLI invocation per major step so the guidance is copy-paste ready rather than descriptive.

Insert a validation checkpoint before generating the final report, e.g. confirm all components were parsed and IOC extraction completed, then emit the JSON report — this adds the feedback loop the multi-step workflow currently lacks.

DimensionReasoningScore

Conciseness

The body is lean — short Overview, tight Prerequisites, and seven terse numbered Steps — and largely assumes Claude's competence rather than explaining basics, matching the score-3 'lean and efficient; every token earns its place' anchor; it is not the score-2 anchor because there is no notable padding or unnecessary explanation.

3 / 3

Actionability

Steps name concrete tools and patterns ('androguard', 'DexClassLoader', 'Runtime.exec') giving some concrete guidance, but provide no executable code or commands and never reference the bundled agent.py that implements them, fitting the score-2 'some concrete guidance but incomplete; missing key details' anchor rather than the score-3 'fully executable; copy-paste ready' anchor.

2 / 3

Workflow Clarity

The seven steps are clearly sequenced, but there are no validation or verification checkpoints between parse/scan/report, and the final report step has no check for completeness, matching the score-2 'steps listed but validation gaps; checkpoints missing or implicit' anchor; it is above the score-1 anchor because the sequence is explicit.

2 / 3

Progressive Disclosure

The body is well-organized into sections and the bundle is shallow (one references/ file and one scripts/ file, one level deep), but the body never links to or signals api-reference.md or agent.py, so navigation to the detail materials is missing — this fits the score-2 'references present but not clearly signaled' anchor rather than the score-3 'well-signaled one-level-deep references' anchor.

2 / 3

Total

9

/

12

Passed

Description

85%

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

The description is strong, specific, and complete with an explicit use trigger and a distinct, well-bounded niche. Its only weakness is trigger-term coverage, which leans technical and misses several natural user phrasings for APK triage.

Suggestions

Add everyday user phrasings to the trigger clause, e.g. 'Use when a user asks to decompile or reverse-engineer an APK, check if an APK is safe or malicious, or triage a suspicious Android app'.

Keep the technical capability list but consider pairing jargon like 'reflection-based API calls' with a plainer synonym so the description matches how non-expert users phrase the request.

DimensionReasoningScore

Specificity

Quotes name multiple concrete actions: 'resource decompilation', 'Java source recovery', 'manifest inspection', 'dangerous permission-combination detection', and 'identification of obfuscated code, dynamic code loading, and reflection-based API calls' — a comprehensive concrete list, matching the score-3 anchor and well above the score-2 'some actions' anchor.

3 / 3

Completeness

It explicitly answers both 'what' (the analysis actions) and 'when' via the explicit trigger clause 'Use to statically triage a suspicious APK without executing it or to build mobile malware detection rules', matching the score-3 anchor; it is not the score-2 anchor because the 'when' is explicit, not implied.

3 / 3

Trigger Term Quality

It includes natural terms like 'Android APK malware', 'suspicious APK', and 'mobile malware detection rules', but leans technical ('reflection-based API calls', 'dynamic code loading') and omits common user phrasings such as 'decompile APK', 'is this APK safe/malicious', or 'Android virus', so it sits at the score-2 'some relevant keywords but missing common variations' anchor rather than full coverage.

2 / 3

Distinctiveness Conflict Risk

The niche is narrow and clearly bounded — static analysis of Android APK malware with named tools (apktool/jadx/androguard) — making it unlikely to trigger for unrelated skills, matching the score-3 'clear niche with distinct triggers' anchor.

3 / 3

Total

11

/

12

Passed

Validation

93%

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

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

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

Warning

Total

15

/

16

Passed

Repository
mukul975/Anthropic-Cybersecurity-Skills
Reviewed

Table of Contents

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