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 agentmods add skills/batteryshark/rekit/bindiffnpx skills add batteryshark/rekit --skill bindiffgit clone --depth 1 https://github.com/batteryshark/rekitWhat 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 | $0.00105 | $0.01274 |
| Opus 5 | $0.00053 | $0.00637 |
| Sonnet 5 | $0.00021 | $0.00255 |
| Haiku 4.5 | $0.00011 | $0.00127 |
Grade A, and why
bindiff 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 2d 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 — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.
BinDiff (binary structural diff)
Match functions across two builds of a binary. BinDiff compares call graphs and control-flow graphs, so it survives recompiles that move every address, reorder functions, and strip every symbol.
When to use
- Patch diffing — a vendor shipped an update; which functions actually changed? The changed list, sorted by ascending similarity, is your bug-hunt worklist.
- Symbol porting — you have a named/debug build and a stripped one. Matched pairs
where only one side has a real name (
portableNames) tell you exactly which symbol goes where. - Variant comparison — two samples from the same family: shared code shows up as high-similarity matches, the new payload as unmatched functions.
- Finding a function again — the routine you reversed last month has moved in the new build. Match old→new and read the pair off the table.
Reach for intellidiff instead when the question is byte or text identity (same file?
which lines changed?). BinDiff answers the structural question that byte diffing cannot.
What it does
- Turns each input into a
.BinExport(BinDiff's disassembly interchange format) using IDA Pro or Ghidra, unless you pass.BinExportfiles directly. - Runs
bindiffto match functions and basic blocks. - Parses the resulting
.BinDiffSQLite database, and reads both.BinExportcall graphs to recover the functions that matched nothing — BinDiff's database records matched pairs only, so added/removed code has to come from the exports.
Static throughout: disassemble, match, report. Neither binary is executed. Disassembler databases go to a temp dir that is deleted afterward, so the sample's own directory is left untouched.
Prerequisites
bindiff— BinDiff 8 (https://github.com/google/bindiff/releases) on PATH.- A disassembler backend, unless both inputs are already
.BinExport:- IDA Pro with the BinExport plugin — the runner drives
idatheadless with-OBinExportAutoAction:BinExportBinary. - Ghidra with the BinExport extension (
BinExport_Ghidra-Java.zip) — the runner drivesanalyzeHeadlesswith the bundled Jython scriptscripts/ghidra_binexport.py.
- IDA Pro with the BinExport plugin — the runner drives
What ships with it
3 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.
- 2d ago First seen · 94 lines · 105 tokens per session scan A 69c8f38ccf46
bindiff is a skill published in the GitHub repository batteryshark/rekit (11 stars, last pushed 24d ago), licensed Apache-2.0. It adds 105 tokens to every session and 1,274 once invoked, about $0.0005 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 2026-08-30.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…