SkillEvaluator v0.9.0 adds eval budgets, dataset checks

// 44m agoPRODUCT UPDATE

SkillEvaluator v0.9.0 adds eval budgets, dataset checks

NVIDIA's open-source framework adds synthetic dataset generation grounded in agent traces, deterministic validation checks, and reusable no-skill baselines. Developers can now enforce hard token and cost budgets while tracking skill improvements across version histories.

// ANALYSIS

As agent skills transition from experimental prompts into production tooling, rigorous evaluation harnesses are becoming table stakes for reliable autonomous systems. SkillEvaluator brings disciplined software testing practices to agent skills by replacing vibe-based prompting with measurable behavioral gates.

–Deterministic checks for script execution, workspace files, and outputs reduce dependency on costly and non-deterministic LLM judges.
–Hard token, judge-call, and dollar budgets halt runaway spend during large evaluation suites while preserving partial results.
–Version-to-version comparisons decouple incremental instruction tweaks from baseline skill lift against vanilla agents.
–Production trace redaction and import provide a direct path to bootstrap realistic, human-verified evaluation benchmarks.

// TAGS

skillevaluatorevaluationbenchmarkagenttestingopen-sourcedevtool

DISCOVERED

44m ago

2026-11-15

PUBLISHED

2d ago

2026-11-13

RELEVANCE

8/ 10

// KEEP READING

More AI developer news from the feed

EXPLORE FULL FEED

UPDATE41m ago

super.engineering slashes memory, CPU after ADEMark

super.engineering rolled out performance optimizations inspired by the new ADEMark benchmark, cutting startup memory by 42% and active agent CPU load from 20% to 8%. The native Rust agent harness also reduced per-chat memory by 40% and tab-naming token usage by 88%.

LAUNCH45m ago

Zap cleans leftover agent git worktrees

Zap is an open-source Go CLI and TUI that automatically detects and clears abandoned Git worktrees left behind by coding agents like Claude Code, Cursor, and Codex. It features interactive safety checks, automatic branch backups, and an undo command to reclaim gigabytes of disk space consumed by duplicated dependencies.

OPEN SOURCE2h ago

GGML hits 1.0, slashes prompt latency

The foundational C/C++ tensor library behind llama.cpp has officially reached version 1.0.0, establishing a stabilized public API alongside significant prefill and inference optimizations. Benchmarks demonstrate immediate performance gains on unchanged hardware, cutting runtime on a 50K-token prompt from 4:22 down to 3:59.