malware-analysis

Use when analyzing suspected malware through static, dynamic, and behavioral techniques, including IOC extraction, YARA or Sigma rules, sandboxing, and anti-analysis behavior.

Quality

86%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

Securityby

Low

Low-risk findings worth noting

Quality

Content

72%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 dense, actionable malware-analysis skill with strong code examples and a clean reference structure, weakened by a padded action-required preamble and an elaborate multi-agent architecture diagram that add tokens without proportional value.

Suggestions

Remove or trim the 'ACTION REQUIRED' preamble and the SentinelHive multi-agent ASCII diagram; they add tokens and reference external files (../field-journal, ../tool-index) that are not part of the bundle.

Add explicit validation/checkpoint notes between phases (e.g., 'if DIE reports a packer, unpack before Phase 2 static analysis') to turn the sequenced phases into a feedback-loop workflow.

Drop the broken external path references (../field-journal/precedent-reverse.md, ../tool-index.md) or replace them with bundle-local files so navigation signals are accurate.

Dimension	Reasoning	Score
Conciseness	The technical core is lean (tables/code, no basic-concept explanations), but the 'ACTION REQUIRED' preamble and the 'SentinelHive' multi-agent ASCII architecture diagram are padding, and the body directs reads of non-bundle paths (../field-journal/precedent-reverse.md, ../tool-index.md).	2 / 3
Actionability	Concrete executable commands (file, strings, rabin2, floss, sha256sum) and complete, copy-paste-ready YARA and Sigma rule examples provide fully actionable guidance.	3 / 3
Workflow Clarity	A clear six-phase sequence plus a final self-check checklist exists, but intermediate per-phase validation checkpoints are implicit rather than explicit feedback loops.	2 / 3
Progressive Disclosure	The body is an overview with three real, well-signaled one-level-deep reference files (yara-sigma-rules.md, sandbox-orchestration.md, anti-analysis-techniques.md) matching the '参考' section, with no deep nesting.	3 / 3
	Total	10 / 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 with an explicit 'Use when' trigger and a comprehensive list of concrete capabilities. It cleanly answers what the skill does and when to invoke it.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions — 'static, dynamic, and behavioral techniques, including IOC extraction, YARA or Sigma rules, sandboxing, and anti-analysis behavior' — matching the 'lists multiple specific concrete actions' anchor.	3 / 3
Completeness	Explicitly answers both 'what' (the analysis techniques enumerated) and 'when' via a 'Use when analyzing suspected malware...' trigger clause, so it is not capped at 2.	3 / 3
Trigger Term Quality	Natural terms a user would say ('analyzing suspected malware', 'YARA', 'Sigma rules', 'sandboxing', 'IOC extraction') give good coverage; not merely technical jargon.	3 / 3
Distinctiveness Conflict Risk	Malware analysis with YARA/Sigma/sandboxing/IOC triggers is a clear niche unlikely to fire for unrelated skills.	3 / 3
	Total	12 / 12 Passed

Validation

100%

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 — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: zhaoxuya520/reverse-skill
Path: skills/malware-analysis/SKILL.md
Commit: 6aa1362

Reviewed: 7 days ago

Table of Contents

Discovery Implementation Validation

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.