analyzing-malware-family-relationships-with-malpedia

Query the Malpedia API to look up malware family aliases and naming (platform.family_name), pull community/vendor YARA rules, link families to threat actors, and map family relationships such as loader-payload chains and shared authorship. Use when researching a malware family's aliases, lineage, or actor attribution, or when sourcing YARA rules for detection.

Quality

82%

Does it follow best practices?

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Securityby

High

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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.

The body is highly actionable with complete executable code and a clear three-step sequence, but it is padded with background explanation, lacks inline validation checkpoints, and fails to leverage its own bundle files via one-level-deep references.

Suggestions

Trim the Overview and Key Concepts to only Malpedia-specific details (the platform.family_name format, relationship types) and remove general malware-classification background Claude already knows.

Add inline validation checkpoints to the workflow (e.g., verify the API response status and that alt_names/attribution are populated before mapping relationships) with a fix-and-retry loop.

Replace the inline API details in Step 1 with a pointer to references/api-reference.md, and reference scripts/agent.py where the full client belongs, so SKILL.md stays an overview with one-level-deep navigation.

Dimension	Reasoning	Score
Conciseness	Mostly efficient with substantial executable code, but the Overview paragraph ("collaborative platform maintained by Fraunhofer FKIE ... over 2,600 malware families ... definitive resource") and parts of Key Concepts explain background Claude largely already knows and could be trimmed.	2 / 3
Actionability	Provides fully executable, copy-paste-ready Python (MalpediaClient, MalwareFamilyMapper, compile_yara_ruleset) with real endpoints, headers, and timeouts — concrete guidance rather than pseudocode.	3 / 3
Workflow Clarity	The three steps are sequenced and a Validation Criteria checklist exists, but there are no inline validation checkpoints or error-recovery loops within the steps, and build_loader_payload_chain relies on a hardcoded known_chains dict rather than API-derived data.	2 / 3
Progressive Disclosure	The body is well-sectioned but duplicates the API reference inline (Step 1) instead of pointing to the existing references/api-reference.md, and never references scripts/agent.py at all; bundle files are present but unsignaled.	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 capabilities, supplies an explicit Use-when trigger, and occupies a distinct niche. It is concise yet comprehensive and free of vague fluff.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions — "look up malware family aliases and naming (platform.family_name)", "pull community/vendor YARA rules", "link families to threat actors", "map family relationships such as loader-payload chains and shared authorship" — rather than vague language.	3 / 3
Completeness	Explicitly answers both what (querying Malpedia API for aliases/YARA/actors/relationships) and when via an explicit "Use when researching a malware family's aliases, lineage, or actor attribution, or when sourcing YARA rules for detection" clause.	3 / 3
Trigger Term Quality	Covers natural terms a user would say — "malware family", "aliases", "YARA rules", "threat actors", "lineage", "actor attribution", and "sourcing YARA rules for detection".	3 / 3
Distinctiveness Conflict Risk	The Malpedia-specific niche and concrete triggers (family aliases, lineage, actor attribution, YARA sourcing) make it clearly distinguishable and unlikely to fire for unrelated skills.	3 / 3
	Total	12 / 12 Passed

Validation

93%

Warnings & errors only

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

Validation — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: mukul975/Anthropic-Cybersecurity-Skills
Path: skills/analyzing-malware-family-relationships-with-malpedia/SKILL.md
Commit: e612f49

Reviewed: 7 days ago

Table of Contents

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