nv:context

nv:context

**Context engineering for engineers who ship.**

npx skills add johnnichev/nv-context -g -y

Auto-detects your tools, commands, and linters. Finds landmines with parallel agents. Generates configs, hooks, session management, and token budgets so every AI coding agent works at maximum effectiveness.

**Live experience:** [skills.nichevlabs.com](https://skills.nichevlabs.com) · production case studies, the research library, and the full synthesis.

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Production Proof

Three real codebases. Same skill. Real numbers.

Repo	Before	After	What changed
selectools (Python SDK, 4,612 tests)	L3, 49/60	L5–L6, 58/60	CLAUDE.md 440 → 67 lines (-85%). Token budget cut 53%.
nichevlabs (multi-product SaaS, orchestrated by selectools)	L4, 17/60	L6, 49/60	SESSION.md 805 → 59 lines (-93%). Saved 15.8K tokens per session. 81 bugs surfaced.
sheriff (Python + TypeScript)	L4, 36/60	L5, 42/60	Incremental polish on an already-strong setup. Coverage gate added.

[Read the full case studies →](https://skills.nichevlabs.com/case-studies)

**Benchmark:** 100% pass rate on 3 test scenarios vs 45.8% baseline (+54.2% delta).

"Most agent failures are not model failures. They are context failures." Philipp Schmid, Google DeepMind

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The Problem

Your AI agent is smart. But it keeps running the wrong test command, touching files it shouldn't, and forgetting your rules mid-session. You've tried writing a CLAUDE.md. Maybe you ran `/init`. It didn't help. Research proves why:

Finding	Source
Auto-generated configs reduce success by 3%	ETH Zurich
Experienced devs are 19% slower with bad AI context	METR Study
40%+ of AI project failures stem from poor context	IntuitionLabs
Using 40% of context window outperforms using 90%	Dex Horthy

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