building-automated-malware-submission-pipeline

Builds an automated malware submission and analysis pipeline that collects suspicious files from endpoints and email gateways, submits them to sandbox environments and multi-engine scanners, and generates verdicts with IOCs for SIEM integration. Use when SOC teams need to scale malware analysis beyond manual sandbox submissions for high-volume alert triage.

Quality

78%

Does it follow best practices?

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Securityby

High

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tessl review fix ./skills/building-automated-malware-submission-pipeline/SKILL.md

Quality

Content

65%Weight 40%Scale 1-5

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 step sequence, but it is verbose (duplicating the bundle script and explaining known concepts) and lacks validation checkpoints and feedback loops for its destructive/batch operations. It also fails to route users to the provided bundle files, inlining their content instead.

Suggestions

Replace the six inline Python blocks with a short 'Quick start' that runs scripts/agent.py and link to references/api-reference.md for endpoint details, keeping only minimal illustrative snippets inline.

Add validation/feedback checkpoints to the orchestrator: verify the sandbox submission succeeded (don't build a verdict on an error dict), confirm IOCs before auto-blocking, and gate destructive blocking behind explicit confirmation or a confidence threshold.

Remove the 'Key Concepts' table entries that restate Dynamic/Static Analysis and Sandbox Evasion, or collapse them to one-line reminders of pipeline-specific behavior.

Dimension	Reasoning	Score
Conciseness	Mostly task-focused but padded: the six large inline Python blocks duplicate scripts/agent.py, and the 'Key Concepts' table explains Dynamic/Static Analysis and Sandbox Evasion that Claude already knows.	3 / 5
Actionability	Fully executable, copy-paste-ready code with concrete API endpoints and thresholds covers the collect → pre-screen → sandbox → verdict → SIEM → block pipeline end to end.	5 / 5
Workflow Clarity	Six steps are clearly sequenced, but the orchestrator performs batch/destructive actions (auto-blocking IPs/domains, auto-submitting samples) with no validation checkpoints or error feedback before blocking, capping this dimension at 3 per the destructive-operations guideline.	3 / 5
Progressive Disclosure	Sections are well-organized, but the body inlines ~470 lines of pipeline code and API detail that duplicate the existing scripts/agent.py and references/api-reference.md without ever signaling or linking to those bundle files.	3 / 5
	Total	14 / 20 Passed

Description

92%Weight 40%Scale 1-5

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: it concisely states a comprehensive set of concrete capabilities and pairs them with an explicit 'Use when...' trigger tied to SOC alert-triage scenarios. The only gap is slightly narrower trigger-term coverage that omits common tool names and synonyms.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions — 'collects suspicious files from endpoints and email gateways, submits them to sandbox environments and multi-engine scanners, and generates verdicts with IOCs for SIEM integration' — giving comprehensive coverage of the pipeline.	5 / 5
Completeness	Explicitly answers what ('Builds an automated malware submission and analysis pipeline...') and when ('Use when SOC teams need to scale malware analysis beyond manual sandbox submissions for high-volume alert triage') with a concrete trigger phrase.	5 / 5
Trigger Term Quality	Includes natural terms a user would say ('malware analysis,' 'sandbox submissions,' 'alert triage,' 'SOC teams') but is missing common synonyms/tool names (e.g., Cuckoo, Any.Run, VirusTotal, 'submit file for scanning') that appear in the tags but not the description.	4 / 5
Distinctiveness Conflict Risk	Targets a clear niche (automated malware triage/submission pipeline for SOC teams) with distinct triggers and minimal overlap risk against other skills.	5 / 5
	Total	19 / 20 Passed

Validation

87%

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 — 14 / 16 Passed

Validation for skill structure

Criteria	Description	Result
skill_md_line_count	SKILL.md is long (508 lines); consider splitting into references/ and linking	Warning
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	14 / 16 Passed

Repository: mukul975/Anthropic-Cybersecurity-Skills
Path: skills/building-automated-malware-submission-pipeline/SKILL.md
Commit: 54a7988

Reviewed: 5 minutes ago

Table of Contents

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