Whole Body Compute (body)
Cut agent token burn and latency with zero accuracy loss on SWE-bench Verified.
Whole Body Compute makes AI computing simpler, faster, and local: giving Claude Code, Cursor, Windsurf, Cline, Goose, and Antigravity a <3ms AST context shield, native macOS vision, and on-device memory right on your Mac (with cross-platform Blood-Brain Barrier & FinOps audit support on Linux).
Open-Core Spec (wholebodycompute.com/open-core) · Zero-Install Spend Audit (audit.py) · Commercial Platform (wholebodycompute.com) · Benchmarks (benchmarks/) · Architecture Wiki
Quickstart
# Option 1: 1-line installer (macOS & Linux)
curl -fsSL https://wholebodycompute.com/begin | sh
# Option 2: uv / pipx directly from GitHub
uv tool install git+https://github.com/wholebodycompute/whole-body-compute.git && body begin
# Option 3: Source checkout
git clone https://github.com/wholebodycompute/whole-body-compute.git
cd whole-body-compute
python3 -m venv .venv && source .venv/bin/activate && pip install -e .
body begin
Or run a read-only 30-day token spend audit across your local agent logs with zero installation:
curl -sSL https://wholebodycompute.com/audit.py | python3
What It Does
Cloud coding agents burn massive context windows re-ingesting full files, noisy test logs, and screenshots on every turn. Whole Body Compute (body) sits locally between your coding agent and macOS/Linux hardware, intercepting bloated reads and tool outputs in <3ms before they hit your cloud billing meter.
┌────────────────────────────────────────────────────────────────────────────────────────┐
│ WHOLE BODY COMPUTE (5 CORE ORGANS) │
├──────────────────────────┬──────────────────────────┬──────────────────────────────────┤
│ 01. THE HEART │ 02. THE BRAINSTEM │ 03. THE EYES & HANDS │
│ Thermal, Perfusion & CSI │ Local Metal, Router & KV │ Foveal AX DOM, Tactile & Vagus │
├──────────────────────────┼──────────────────────────┴──────────────────────────────────┤
│ 04. THE HIPPOCAMPUS │ 05. THE IMMUNE SYSTEM (BLOOD-BRAIN BARRIER) │
│ Memory WAL, Flush & REM │ Pre/Post Hooks, SensoryVector, <3ms AST Slicer & SecGate │
└──────────────────────────┴─────────────────────────────────────────────────────────────┘
| Capability | Standard Unshielded Cloud Agent | With Whole Body Compute (body) |
Measured Impact |
|---|---|---|---|
| Harness Wiring | Manual per-editor rules & scattered scripts | body begin auto-wires PreToolUse / PostToolUse hooks across Claude Code, Cursor, Antigravity, Windsurf, Cline & Goose |
60-second setup + 30-day FinOps receipt |
| File & Log Reads | Unbounded read_file (2,000+ lines) & raw pytest/cat dumps |
Blood-Brain Barrier (<3ms AST Symbol Slicer) + local Metal ReconScout |
Up to 98.7% token reduction on large reads |
| Desktop Vision | Full-screen PNG loops (7,650+ tokens/step) or heavy 24/7 video recorders |
Foveal Vision (AXUIElement DOM) + <50ms Tactile git/file delta sensor (<50MB RAM) |
96.9%–99.5% sensory token reduction |
| Session Hygiene | $O(N^2)$ turn accumulation until context degrades | Cognitive Sentry (body context) + StateCapsule Flush (body flush) [Pro] |
Zero-loss handoff in <30 steps |
| Pre-Egress Security | Cloud classifiers run after data leaves your machine | <1ms 23-vendor secret redaction, 1Password/Keychain blindfold, <2ms APFS CoW airlock & AST SecGate |
0 secret leaks · 0.0% ASR on AgentDojo |
Benchmarks (SWE-bench Verified & Princeton HAL)
Evaluated across 146 live unscripted agent sessions (including 100 official upstream princeton-nlp/SWE-bench_Verified runs across 10 Python organizations at untouched historical commits, graded strictly against held-out FAIL_TO_PASS + PASS_TO_PASS test patches):
| Evaluation Suite | Baseline (Unshielded) | + Whole Body Compute |
Key Empirical Result |
|---|---|---|---|
SWE-bench Verified (k=3, 60 Live Trials)Gemini 4 Carbon across 10 official orgs |
30/30 (100% Pass@1)10/10 Pass^3 · 203.08M ctx |
30/30 (100% Pass@1)10/10 Pass^3 · 137.23M ctx |
Zero accuracy loss (100% strict 3/3 consistency), -32.4% total context (-65.85M tokens), -25.6% billed input, -18.8% fewer turns |
SWE-bench Verified (Claude Code 2x2, 40 Runs)Claude Sonnet & Claude Haiku CLI |
Vanilla Sonnet: 9/10 ($4.00)Vanilla Haiku: 8/10 ($4.42) |
Sonnet + WBC: 10/10 ($3.89)Haiku + WBC: -36.1% ctx ($3.05) |
Sonnet + WBC solved 10/10 (100%) and cost -12.0% LESS than Vanilla Haiku ($3.89 vs. $4.42) while beating it by +20.0pp accuracy |
Multi-Track Live A/B (18 Sessions)SWE-bench + CORE-Bench Hard + OSWorld |
Haiku 4.5: 9/9 (100%)5.26M ctx · $1.60 · 312.9s |
Haiku 4.5 + WBC: 9/9 (100%)1.55M ctx · $0.51 · 190.5s |
-67.8% API spend (3.11x efficiency), -71.9% billed input, -39.1% faster wall-clock time |
Security & Reliability (AgentDojo + CyberSecEval 3) |
100.0% Attack Success (12/12) |
0.0% Attack Success (12/12 blocked) |
0.0% false-positive rate (6/6 benign passed), 0.102ms in-process gate overhead |
Full per-repository tables, 2x2 model matrices (Sonnet, Haiku, Gemini, GPT-OSS 120B), raw JSON telemetry receipts, and 1-command verification harnesses: benchmarks/README.md.
CLI Reference (body)
# Core Onboarding, Audit & Organ Primitives (Free Forever)
body begin # Wire Blood-Brain Barrier hooks & print 30-day FinOps ROI receipt
body audit-spend # Scan Claude Code, Cursor, Antigravity, Windsurf, Cline, Goose, Codex & Aider spend
body savings # Inspect live Blood-Brain Barrier token savings & active shield status
body report # 5-Pillar operational & FinOps scorecard (Session, 24h & 7d trends)
body doctor # Sub-second 5-organ health check (--exercise runs closed-loop reflex verification)
body heart # Thermal state, Unified RAM headroom & model perfusion status
body eyes # Live macOS AXUIElement Foveal DOM snapshot + on-demand Apple Vision OCR
body hands # Deterministic UI actuation (ax_act) & <50ms tactile git/file delta sensor
body immune # Blood-Brain Barrier audit log (--window 24h --tools --blocked), APFS CoW & SecGate
body daemon status # Manage portable macOS LaunchAgents (install / status / logs)
# Sovereign Context, Memory & Autonomous Consolidation [Pro / Team]
body license # Activate Pro/Team Polar key (--activate <KEY>) or inspect tier quota
body context # Context Saturation Index (CSI) & bloat attribution (--insights) [Pro]
body flush --auto # Grounded StateCapsule session handoff & metabolic noise purge [Pro]
body memory # Persistent Hippocampus SQLite WAL & FTS5 recall (--remember / --recall) [Pro]
body perfusion # Evict idle local Metal models (--evict) or pre-warm weights (--prewarm) [Pro]
body sleep # Nocturnal REM consolidation & Radix KV-Cache prefix digest [Pro]
Deep-dive component reference and glossary: docs/WIKI_AND_GLOSSARY.md.
License
Free forever for individual developers, researchers, and internal non-competing business use under the Open-Core Community License (LICENSE) and PATENTS.md - commercial resale, managed hosting, or embedding into competing IDEs, agent harnesses, gateways, or FinOps products requires a separate commercial license (hello@wholebodycompute.com).
Metadata
Release files for whole-body-compute 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| whole_body_compute-0.1.0.tar.gz | 1.0 MB | With provenance | Details for whole_body_compute-0.1.0.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| whole_body_compute-0.1.0-py3-none-any.whl | Python 3 | none | any | Details for whole_body_compute-0.1.0-py3-none-any.whl |
Total release size: 2.0 MB
Release files / whole_body_compute-0.1.0.tar.gz
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| Tags | Source |
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| Size | 1.0 MB |
| Tags | Python 3 |
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| Uploaded via |
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