Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add mattmre/EVOKORE-MCP-PUBLIC --skill reverse-engineering-workbenchgit clone --depth 1 https://github.com/mattmre/EVOKORE-MCP-PUBLICWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/mattmre/evokore-mcp-public/reverse-engineering-workbench)<a href="https://agentmods.dev/skills/mattmre/evokore-mcp-public/reverse-engineering-workbench"><img src="https://agentmods.dev/badge/skills/mattmre/evokore-mcp-public/reverse-engineering-workbench/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/mattmre/evokore-mcp-public/reverse-engineering-workbench"><img src="https://agentmods.dev/badge/skills/mattmre/evokore-mcp-public/reverse-engineering-workbench.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00055 | $0.01026 |
| Opus 5 | $0.00028 | $0.00513 |
| Sonnet 5 | $0.00011 | $0.00205 |
| Haiku 4.5 | $0.00006 | $0.00103 |
Grade A, and why
reverse-engineering-workbench scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reverse Engineering Workbench
Coordinate reverse-engineering work as a staged workflow instead of jumping straight into decompilation. Select the right tool family, define the evidence needed, and move from reconnaissance to semantic recovery to debugger confirmation.
Use When
- Opening an unfamiliar executable, shared library, driver, or firmware blob
- Planning how to divide work between Ghidra-style static analysis and debugger sessions
- Building a repeatable workflow for decompilation, renaming, xref chasing, and malware triage
- Deciding whether a task should stay in EVOKORE skills or call proxied child tools directly
Core Rule Set
- Start with reconnaissance before renaming or patching.
- Prefer static evidence first: imports, exports, strings, call graph shape, and decompiler output.
- Escalate to dynamic analysis only when static analysis leaves behavior ambiguous.
- Rename and retype only after collecting enough evidence to defend the new meaning.
- Keep a short findings log: target, hypothesis, supporting evidence, unresolved questions, next pivot.
EVOKORE Tool Activation Pattern
Run discover_tools first so the right child-tool families become visible for the session.
Suggested discovery prompts:
ghidra headless reverse engineering decompile xrefs strings imports exportsbinary analysis debugger x64dbg windbg malware triage pe dotnetreva ghidra assistant reverse engineering
Expected tool families:
ghidra_headless_*for structured static analysis, decompilation, xrefs, types, comments, and patchingbinary_analysis_*for static triage, .NET work, control flow, malware heuristics, YARA, x64dbg, and WinDbgreva_*for assistant-style Ghidra workflows if the ReVa child server is enabled
Recommended Workflow
- Run
reverse-engineering-company-systemif the target is large, ambiguous, or likely to span multiple RE lanes. - Run
unknown-binary-onboardingto choose the right specialist tools and produce the first target queue. - Run
ghidra-core-reconto map functions, strings, imports, exports, and likely entry points. - Run
ghidra-function-analysisorsemantic-recovery-campaignon priority routines and subsystems. - Run
ghidra-rename-and-retypeto clean names, signatures, variables, comments, and data types. - Run
debugger-driven-analysisif runtime-only behavior, unpacking, crypto state, IPC, or anti-analysis logic remains unclear. - Run
malware-triage-workflowif the sample is suspicious, packed, or clearly malicious. - Run
reverse-engineering-improvement-loopafter meaningful milestones so future sessions inherit the lessons instead of relearning them.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 82 lines · 55 tokens per session scan A 7d3236fdab69
reverse-engineering-workbench is a skill published in the GitHub repository mattmre/EVOKORE-MCP-PUBLIC (3 stars, last pushed 3mo ago), licensed MIT. It adds 55 tokens to every session and 1,026 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
analyzing-golang-malware-with-ghidra
Reverse engineer Go-compiled malware using Ghidra with specialized scripts for function recovery, string extraction, and type reconstruction in stripped Go binaries.
analyzing-golang-malware-with-ghidra
Reverse engineer Go-compiled malware in Ghidra by parsing Go buildinfo and pclntab structures, recovering stripped/obfuscated function names (e.g. via GoResolver), and extracting embedded module/dependency strings and types from Go binaries. Use when analyzing a Go-language malware sample, deobfuscating a…
deobfuscating-powershell-obfuscated-malware
Systematically deobfuscate multi-layer PowerShell malware using AST analysis, dynamic tracing, and tools like PSDecode and PowerDecode to reveal hidden payloads and C2 infrastructure.
investigating-ransomware-attack-artifacts
Identify, collect, and analyze ransomware attack artifacts to determine the variant, initial access vector, encryption scope, and recovery options.
analyzing-golang-malware-with-ghidra
Reverse engineer Go-compiled malware using Ghidra with specialized scripts for function recovery, string extraction, and type reconstruction in stripped Go binaries.
ts-debug
TypeScript/Node debugging expert. Use when the user needs to debug, profile, or trace TypeScript or Node.js code — e.g. "how do I debug this", "find the memory leak", "why is this slow", "add a breakpoint", "profile this function", "why won't the process exit".