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analyzing-apt-group-with-mitre-navigator

Query ATT&CK data with attackcti, mitreattack-python, and stix2, then build MITRE ATT&CK Navigator layers and multi-layer heatmap overlays mapping one or more APT groups' TTPs for detection-gap analysis. Use to compare threat-actor technique coverage, find gaps in detection engineering, or produce Navigator visualizations for threat-intel reporting.

68

Quality

82%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

65%Weight 40%Scale 1-3

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

A highly actionable skill with five complete, executable code examples and a clear step sequence, weakened by explanatory prose Claude does not need, a detached validation section, and bundle files (api-reference.md, agent.py) that are never linked from the body.

Suggestions

Trim the Overview and Key Concepts sections to domain-specific detail only (layer v4.5 fields, G-code conventions) and drop generic explanations of what ATT&CK/Navigator are; rewrite the templated 'When to Use' bullets into concrete triggers.

Reference the existing bundle files from the body — e.g. 'Full layer-format and TAXII/STIX details: see [references/api-reference.md]' and 'Reusable agent: see [scripts/agent.py]' — so the inline steps can point to rather than duplicate them.

Move validation inline as checkpoints (e.g. after generating a layer, load it back / validate JSON against the v4.5 schema and only proceed when valid) to turn the criteria list into a feedback loop.

DimensionReasoningScore

Conciseness

The five code blocks earn their place, but the Overview and Key Concepts sections re-explain ATT&CK/Navigator concepts Claude already knows, and the 'When to Use' bullets read as generic templated phrasing ('analyzing apt group with mitre navigator'). It is mostly efficient but could be tightened.

2 / 3

Actionability

Each of the five steps provides complete, executable Python (attackcti queries, layer JSON generation, set-based group comparison, gap-layer construction, tactic breakdown) that is copy-paste ready with real ATT&CK IDs and field names.

3 / 3

Workflow Clarity

Steps are clearly sequenced (Step 1–5), but validation lives in a separate post-hoc 'Validation Criteria' list rather than inline checkpoints, and there are no 'validate → fix → retry' feedback loops within the flow.

2 / 3

Progressive Disclosure

Bundle files references/api-reference.md and scripts/agent.py exist but are never referenced or signaled in the body, and the inline Step 1–5 code largely duplicates what the script already provides — content that should be split out stays inline.

2 / 3

Total

9

/

12

Passed

Description

100%Weight 40%Scale 1-3

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

A strong, third-person description that names concrete tools and actions, includes explicit 'Use to...' trigger guidance, and occupies a clearly distinct threat-intelligence niche. No vague fluff or over-claims.

DimensionReasoningScore

Specificity

Names the concrete tools (attackcti, mitreattack-python, stix2) and lists multiple specific actions — querying data, building Navigator layers, multi-layer heatmap overlays, mapping TTPs, and detection-gap analysis — matching the 'multiple specific concrete actions' anchor.

3 / 3

Completeness

Explicitly answers 'what' (query/build/map/analyze) and 'when' via a clear 'Use to compare... find gaps... or produce Navigator visualizations' trigger clause.

3 / 3

Trigger Term Quality

Covers natural domain terms a threat-intel analyst would actually say: 'APT groups', 'TTPs', 'MITRE ATT&CK Navigator', 'detection-gap', 'threat-actor', 'threat-intel reporting'.

3 / 3

Distinctiveness Conflict Risk

Occupies a clear niche (ATT&CK Navigator layers + APT TTP detection-gap analysis) with distinct triggers unlikely to fire for unrelated skills.

3 / 3

Total

12

/

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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