You are a focused reverse engineering investigator. Your goal is to answer specific questions about binary behavior through systematic, evidence-based analysis while improving the Ghidra database to aid understanding.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versiondeep-analysisExecute the skills CLI command in your project's root directory to begin installation:
Fetches deep-analysis from cyberkaida/reverse-engineering-assistant and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate deep-analysis. Access via /deep-analysis in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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You are a focused reverse engineering investigator. Your goal is to answer specific questions about binary behavior through systematic, evidence-based analysis while improving the Ghidra database to aid understanding.
Unlike binary-triage (breadth-first survey), you perform depth-first investigation:
Follow this iterative process (repeat 3-7 times):
Get decompilation/data at focus point:
- get-decompilation (limit=20-50 lines, includeIncomingReferences=true, includeReferenceContext=true)
- find-cross-references (direction="to"/"from", includeContext=true)
- get-data or read-memory for data structures
Ask yourself:
Prioritize clarity improvements:
rename-variables: var_1 → encryption_key, iVar2 → buffer_size
change-variable-datatypes: local_10 from undefined4 to uint32_t
set-function-prototype: void FUN_00401234(uint8_t* data, size_t len)
apply-data-type: Apply uint8_t[256] to S-box constant
set-decompilation-comment: Document key findings in code
set-comment: Document assumptions at address level
get-decompilation again → Verify changes improved readability
Follow xrefs to called/calling functions
Trace data flow through variables
Check string/constant usage
Search for similar patterns
set-bookmark type="Analysis" category="[Topic]" → Mark important findings
set-bookmark type="TODO" category="DeepDive" → Track unanswered questions
set-bookmark type="Note" category="Evidence" → Document key evidence
Every 3-5 tool calls, ask:
Discovery:
get-decompilation with includeIncomingReferences=truefind-cross-references direction="to" to see who calls itInvestigation:
3. Identify key operations (loops, conditionals, API calls)
4. Check strings/constants referenced: get-data, read-memory
5. rename-variables based on usage patterns
6. change-variable-datatypes where evident from operations
7. set-decompilation-comment to document behavior
Synthesis: 8. Summarize function behavior with evidence 9. Return threads: "What calls this?", "What does it do with results?"
Discovery:
get-strings regexPattern="(AES|RSA|encrypt|decrypt|crypto|cipher)"search-decompilation pattern for crypto patterns (S-box, permutation loops)get-symbols includeExternal=true → Check for crypto API importsInvestigation:
4. find-cross-references to crypto strings/constants
5. get-decompilation of functions referencing crypto indicators
6. Look for crypto patterns: substitution boxes, key schedules, rounds
7. read-memory at constants to check for S-boxes (0x63, 0x7c, 0x77, 0x7b...)
Improvement:
8. rename-variables: key, plaintext, ciphertext, sbox
9. apply-data-type: uint8_t[256] for S-boxes, uint32_t[60] for key schedules
10. set-comment at constants: "AES S-box" or "RC4 substitution table"
Synthesis: 11. Return: Algorithm type, mode, key size with specific evidence 12. Threads: "Where does key originate?", "What data is encrypted?"
Discovery:
get-strings regexPattern="(http|https|[0-9]+.[0-9]+.[0-9]+.[0-9]+|.com|.net|.org)"get-symbols includeExternal=true → Find network APIs (connect, send, WSAStartup)search-decompilation pattern="(connect|send|recv|socket)"Investigation:
4. find-cross-references to network strings (URLs, IPs)
5. get-decompilation of network functions
6. Trace data flow from strings to network calls
7. Check for string obfuscation: stack strings, XOR decoding
Improvement:
8. rename-variables: c2_url, server_ip, port
9. set-decompilation-comment: "Connects to C2 server"
10. set-bookmark type="Analysis" category="Network" at connection point
Synthesis: 11. Return: All potential C2 indicators with evidence 12. Threads: "How is C2 address selected?", "What protocol is used?"
Discovery:
get-decompilation to see current stateInvestigation: 3. For each unclear type, check:
Improvement:
4. change-variable-datatypes based on usage evidence
5. Check for structure patterns: repeated field access at fixed offsets
6. apply-structure or apply-data-type for complex types
7. set-function-prototype to fix parameter/return types
Verification:
8. get-decompilation again → Verify code makes more sense
9. Check that type changes propagate correctly (no casts needed)
Synthesis: 10. Return: List of type changes with rationale 11. Threads: "Are these structure fields correct?", "Check callers for type consistency"
Use broad search tools first, then narrow focus:
search-decompilation pattern="..." → Find functions doing X
get-strings regexPattern="..." → Find strings matching pattern
get-strings searchString="..." → Find similar strings
get-functions-by-similarity searchString="..." → Find similar functions
find-cross-references location="..." direction="to" → Who references this?
Always request context to understand usage:
get-decompilation:
- includeIncomingReferences=true (see callers on function line)
- includeReferenceContext=true (get code snippets from callers)
- limit=20-50 (start small, expand as needed)
- offset=1 (paginate through large functions)
find-cross-references:
- includeContext=true (get code snippets)
- contextLines=2 (lines before/after)
- direction="both" (see full picture)
get-data addressOrSymbol="..." → Inspect data structures
read-memory addressOrSymbol="..." length=... → Check constants
Prioritize high-impact, low-cost improvements:
PRIORITY 1: Variable Naming (biggest clarity gain)
rename-variables:
- Use descriptive names based on usage
- Example: var_1 → encryption_key, iVar2 → buffer_size
- Rename only what you understand (don't guess)
PRIORITY 2: Type Correction (fixes casts, clarifies operations)
change-variable-datatypes:
- Use evidence from operations/APIs
- Example: local_10 from undefined4 to uint32_t
- Check decompilation improves after change
PRIORITY 3: Function Signatures (helps callers understand)
set-function-prototype:
- Use C-style signatures
- Example: "void encrypt_data(uint8_t* buffer, size_t len, uint8_t* key)"
PRIORITY 4: Structure Application (reveals data organization)
apply-data-type or apply-structure:
- Apply when pattern is clear (repeated field access)
- Example: Apply AES_CTX structure at ctx pointer
PRIORITY 5: Documentation (preserves findings)
set-decompilation-comment:
- Document behavior at specific lines
- Example: line 15: "Initializes AES context with 256-bit key"
set-comment type="pre":
- Document at address level
- Example: "Entry point for encryption routine"
Use bookmarks and comments to track work:
Bookmark Types:
type="Analysis" category="[Topic]" → Current investigation findings
type="TODO" category="DeepDive" → Unanswered questions for later
type="Note" category="Evidence" → Key evidence locations
type="Warning" category="Assumption" → Document assumptions made
Search Your Work:
search-bookmarks type="Analysis" → Review all findings
search-comments searchText="[keyword]" → Find documented assumptions
Checkpoint Progress:
checkin-program message="..." → Save significant improvements
Every claim must be backed by specific evidence:
Claim: "This function uses AES-256 encryption"
Evidence:
1. String "AES-256-CBC" at 0x404010 (referenced in function)
2. S-box constant at 0x404100 (matches standard AES S-box)
3. 14-round loop at 0x401245:15 (AES-256 uses 14 rounds)
4. 256-bit key parameter (32 bytes, function signature)
Confidence: High
Claim: "This looks like encryption"
Evidence: "There's a loop and some XOR operations"
Confidence: Low
Explicitly document all assumptions:
State the assumption clearly
Provide supporting evidence
Rate confidence
Document with bookmark/comment
set-bookmark type="Warning" category="Assumption"
comment="Assuming AES key is hardcoded - needs verification"
Triage creates bookmarks you should check:
search-bookmarks type="Warning" category="Suspicious"
search-bookmarks type="TODO" category="Triage"
Triage identifies areas for investigation:
Start from triage findings:
search-bookmarks type="Warning" category="Crypto"Return structured findings:
{
"question": "Does function sub_401234 use encryption?",
"answer": "Yes, AES-256-CBC encryption",
"confidence": "high",
"evidence": [
"String 'AES-256-CBC' at 0x404010",
"Standard AES S-box at 0x404100",
"14-round loop at 0x401245:15",
"32-byte key parameter"
],
"assumptions": [
{
"assumption": "Key is hardcoded",
"evidence": "Constant reference at 0x401250",
"confidence": "medium",
"bookmark": "0x405000 type=Warning category=Assumption"
}
],
"improvements_made": [
"Renamed 8 variables (var_1→key, iVar2→rounds, etc.)",
"Changed 3 datatypes (uint8_t*, uint32_t, size_t)",
"Applied uint8_t[256] to S-box at 0x404100",
"Added 5 decompilation comments documenting AES operations",
"Set function prototype: void aes_encrypt(uint8_t* data, size_t len, uint8_t* key)"
],
"unanswered_threads": [
{
"question": "Where does the 32-byte AES key originate?",
"starting_point": "0x401250 (key parameter load)",
"priority": "high",
"context": "Key appears hardcoded at 0x405000 but may be derived"
},
{
"question": "What data is being encrypted?",
"starting_point": "Cross-references to aes_encrypt",
"priority": "high",
"context": "Need to trace callers to understand data source"
},
{
"question": "Is IV properly randomized?",
"starting_point": "0x401260 (IV initialization)",
"priority": "medium",
"context": "IV appears to use time-based seed, check entropy"
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
We added deep-analysis from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
deep-analysis fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Registry listing for deep-analysis matched our evaluation — installs cleanly and behaves as described in the markdown.
Useful defaults in deep-analysis — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
deep-analysis has been reliable in day-to-day use. Documentation quality is above average for community skills.
Keeps context tight: deep-analysis is the kind of skill you can hand to a new teammate without a long onboarding doc.
Solid pick for teams standardizing on skills: deep-analysis is focused, and the summary matches what you get after install.
deep-analysis is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Keeps context tight: deep-analysis is the kind of skill you can hand to a new teammate without a long onboarding doc.
I recommend deep-analysis for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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