analyzing-malware-family-relationships-with-malpedia
Use the Malpedia platform and API to research malware family relationships, track variant evolution, link families to threat actors, and integrate YARA rules for detection across malware lineages.
50
55%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Risky
Do not use without reviewing
Optimize this skill with Tessl
npx tessl skill review --optimize ./skills/analyzing-malware-family-relationships-with-malpedia/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 description with excellent specificity and distinctiveness, clearly naming the Malpedia platform and listing concrete actions like tracking variant evolution and integrating YARA rules. The main weakness is the absence of an explicit 'Use when...' clause, which would help Claude know exactly when to select this skill over others.
Suggestions
Add a 'Use when...' clause with trigger phrases like 'Use when the user asks about malware families, threat actor attribution, YARA rule integration, or references Malpedia.'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: research malware family relationships, track variant evolution, link families to threat actors, and integrate YARA rules for detection across malware lineages. | 3 / 3 |
Completeness | Clearly answers 'what does this do' with specific actions, but lacks an explicit 'Use when...' clause or equivalent trigger guidance, which caps this dimension at 2 per the rubric. | 2 / 3 |
Trigger Term Quality | Includes strong natural keywords users would say: 'Malpedia', 'malware family', 'threat actors', 'YARA rules', 'variant evolution', 'malware lineages', 'detection'. These are terms a security researcher would naturally use. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive due to the specific mention of 'Malpedia platform and API', combined with the niche domain of malware family research, YARA rules, and threat actor linking. Unlikely to conflict with other skills. | 3 / 3 |
Total | 11 / 12 Passed |
Implementation
27%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The skill provides a reasonably complete API client and analysis framework for Malpedia but suffers from significant verbosity, explaining concepts Claude already knows and including boilerplate sections. The workflow lacks validation checkpoints and error handling, and all content is crammed into a single file without progressive disclosure. The code is mostly functional but includes some hardcoded workarounds rather than truly dynamic relationship discovery.
Suggestions
Remove the 'Key Concepts' section entirely or reduce to a 2-line summary—Claude already understands malware families, naming conventions, and relationship types.
Add explicit validation steps within the workflow: verify API connectivity before proceeding, validate YARA rule compilation with `yara.compile()`, and add error handling for rate limits and missing data.
Extract the full class implementations into separate bundle files (e.g., `malpedia_client.py`, `family_mapper.py`) and keep only concise usage examples in SKILL.md.
Remove the generic 'When to Use' section and trim the overview to 1-2 sentences focused on what's unique about this skill's approach.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is verbose with unnecessary explanations Claude already knows (what Malpedia is, what malware families are, platform naming conventions, relationship types). The 'Key Concepts' section explains basic malware classification concepts that are common knowledge for Claude. The 'When to Use' section is generic boilerplate. The overview paragraph restates information that could be omitted entirely. | 1 / 3 |
Actionability | The code is mostly executable and well-structured with a proper API client class, but the `build_loader_payload_chain` method uses hardcoded known chains rather than actually deriving relationships from the API, making it more pseudocode-like in practice. The YARA compilation function makes assumptions about the API response format without handling edge cases. The code is functional but has gaps in real-world applicability. | 2 / 3 |
Workflow Clarity | Steps are listed sequentially (query API, map relationships, extract YARA rules) but there are no validation checkpoints between steps. No error recovery or feedback loops exist—e.g., what happens if the API key is invalid, rate limits are hit, or YARA rules fail to compile. The 'Validation Criteria' section is a checklist of outcomes rather than integrated verification steps within the workflow. | 2 / 3 |
Progressive Disclosure | This is a monolithic wall of text with no bundle files to offload detailed content. The full API client implementation, relationship mapper, and YARA compiler are all inline when they could be in separate referenced files. The Key Concepts section adds significant length that could be a separate reference. References section links to external resources but doesn't organize internal content across files. | 1 / 3 |
Total | 6 / 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
0445030
- Reviewed
Table of Contents
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