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memory-forensics

Master memory forensics techniques including memory acquisition, process analysis, and artifact extraction using Volatility and related tools. Use when analyzing memory dumps, investigating incidents, or performing malware analysis from RAM captures.

67

Quality

84%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

68%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 content is highly actionable with executable commands but is a monolithic wall of references with weak progressive disclosure and workflows that lack validation checkpoints for batch/forensic operations.

Suggestions

Add explicit validation checkpoints to the Malware Analysis and Incident Response workflows (e.g., verify dump size/hash after acquisition, confirm plugin output before proceeding) with fix-and-retry feedback loops.

Split the large reference material (Volatility plugin catalog, Windows data structures, YARA rule library) into separate files under references/ and link to them one level deep from SKILL.md.

Trim or externalize the inlined C struct definitions unless directly needed for an actionable step, to reduce token load.

DimensionReasoningScore

Conciseness

The body is mostly lean command catalogs that assume Claude's competence, though the inlined C struct definitions (EPROCESS/PEB/MMVAD) and a few explanatory comments add padding that could be trimmed.

4 / 5

Actionability

Provides copy-paste-ready, executable Volatility commands and scripts covering acquisition, analysis plugins, workflows, and YARA rules across Windows/Linux/macOS.

5 / 5

Workflow Clarity

The Malware Analysis and Incident Response workflows list numbered steps but lack explicit validation checkpoints or error-recovery feedback loops between steps, which the rubric caps at 3 for batch/forensic operations.

3 / 5

Progressive Disclosure

A ~485-line monolithic file inlines content (plugin references, data structures, YARA rules) that belongs in separate reference files, with no bundle files or external references to offload it.

2 / 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 concrete, third-person, and clearly answers both what the skill does and when to use it, with strong trigger phrasing. Minor gaps in synonym/extension coverage prevent a perfect trigger-term score.

DimensionReasoningScore

Specificity

Names concrete actions ("memory acquisition, process analysis, and artifact extraction") and a specific tool ("Volatility"), giving comprehensive coverage of the skill's capabilities.

5 / 5

Completeness

Explicitly answers both "what" (acquisition, process analysis, artifact extraction via Volatility) and "when" ("Use when analyzing memory dumps, investigating incidents, or performing malware analysis from RAM captures").

5 / 5

Trigger Term Quality

Includes natural terms ("memory dumps", "investigating incidents", "malware analysis", "RAM captures") but misses common synonyms and file extensions such as "memory forensics", ".raw", ".dmp", or "crash dump".

4 / 5

Distinctiveness Conflict Risk

Targets a clear niche (memory forensics from RAM captures via Volatility) with distinct triggers and minimal overlap risk against other skills.

5 / 5

Total

19

/

20

Passed

Validation

100%

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

rmyndharis/antigravity-skills

Path

skills/memory-forensics/SKILL.md

Reviewed

Table of Contents

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