What
v1.4.2 was published to npm with workspace-style dependency references (workspace:* and file:../core) that work in monorepo development but break npm install for end users. v1.4.3 fixes the dependency metadata across all 4 packages.
All v1.4.2 features, logic, and benchmark-validated behavior are unchanged.
Empirical Validation: 20,000+ API Calls Across 13+ LLMs
TSCG is backed by one of the largest independent tool-schema compression benchmarks in the ecosystem:
- 20,000+ real API calls across controlled A/B experiments
- 13+ language models tested: Claude Opus 4.7, Claude Sonnet 4, GPT-4o, GPT-4o-mini, GPT-5.2, GPT-5.4, GPT-5.5, Qwen3-32B, Qwen3-14B, Phi-4-mini, Llama 3.1 8B, Gemma 3 12B, DeepSeek-v3
- 3 frontier API providers: Anthropic, OpenAI, Ollama (local)
- 7 sub-15B open-weight models validated for local deployment
- Per-operator isolation sweeps: 9-condition leave-one-in probes identifying per-model operator sensitivity
- Combination-effect detection: discovery of super-additive negative interactions (Scenario B) in GPT-5.5
- External validation: BFCL benchmark (108-181% accuracy retention), ToolBench, API-Bank
Key findings:
- 45-62% token savings with accuracy retention or improvement across model families
- Per-model operator sensitivity is real: GPT-5.4 is config-robust (CFO +15pp), GPT-5.5 is combination-fragile
- Small models (4B-14B) benefit from compression even more than frontier models
See findings/ for the complete empirical research library.
Impact
If you installed any @tscg/* package at v1.4.2, you may have hit errors like:
npm ERR! Could not resolve workspace:* dependencynpm ERR! ENOENT file:../core
v1.4.3 resolves this:
npm install @tscg/openclaw@1.4.3
What Changed (v1.4.3 vs v1.4.2)
Metadata-only fix:
@tscg/openclaw: dep reffile:../core->^1.4.3@tscg/mcp-proxy: dev-dep refworkspace:*->^1.4.3@tscg/tool-optimizer: dev-dep refworkspace:*->^1.4.3- All packages: peer-dep refs bumped ->
^1.4.3
No source code changes. No behavioral differences from v1.4.2.
v1.4.2 Features (All Included in v1.4.3)
- Per-operator adaptive sweep (
tune --sweep) -- 9-condition isolation testing (180 calls, ~USD 1) - Combination-effect detection (Scenario B) -- automatic fallback for fragile model configurations
selectOptimalProfile()-- derives optimal operator set from per-operator deltas with classification thresholds- mcp-proxy
cacheReaderintegration -- adaptive profiles from openclaw sweep override static profiles at runtime - GPT-5.4 + GPT-5.5 static profiles in mcp-proxy, derived from 440-call benchmark
- 459+ tests across all packages
Deprecated
v1.4.2 on npm has been deprecated. Users should upgrade to v1.4.3.