Context Engineering Kit is a collection of skills, agents, hooks, instructions, commands, and plugins that shape how coding agents use context and carry out development work. It is for developers using Claude Code and other supported coding agents who want more predictable results. The catalogue entries are components from this collection.
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 skills add NeoLabHQ/context-engineering-kit --skill write-testsgit clone --depth 1 https://github.com/NeoLabHQ/context-engineering-kitWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/neolabhq/context-engineering-kit/write-tests)<a href="https://agentmods.dev/skills/neolabhq/context-engineering-kit/write-tests"><img src="https://agentmods.dev/badge/skills/neolabhq/context-engineering-kit/write-tests/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/neolabhq/context-engineering-kit/write-tests"><img src="https://agentmods.dev/badge/skills/neolabhq/context-engineering-kit/write-tests.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector pass
What 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 5.1 | $0.00050 | $0.01773 |
| Opus 5 | $0.00025 | $0.00886 |
| Sonnet 5 | $0.00010 | $0.00355 |
| Haiku 4.5 | $0.00005 | $0.00177 |
Grade A, and why
write-tests 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 7d 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.
The source is not reproduced here
Licensed GPL-3.0
The repository is licensed GPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
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.
- 7d ago First seen · 214 lines · 50 tokens per session scan A 027b51c8b448
write-tests is a skill published in the GitHub repository NeoLabHQ/context-engineering-kit (1,682 stars, last pushed 14d ago), licensed GPL-3.0. It adds 50 tokens to every session and 1,773 once invoked, about $0.0003 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 2026-09-03.
Other skills, from other repositories
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Vitest review (@repo/vitest-config node/workers presets, Cloudflare Vitest pool, testing split) against current official Vitest and Cloudflare best practices. USE WHEN: user runs /review-vitest or explicitly asks for this review. DO NOT USE WHEN: reviewing app code, other dev dependencies, or implementing features.
Agent Evaluation Framework Builder
Designs an eval suite for an LLM agent or pipeline including success metrics, trajectory scoring, LLM-as-judge setup, and regression test cases.
Edge Case Discovery
Systematically identifies edge cases and boundary conditions for any function, API, or user flow.
Flaky Test Analyzer
Diagnoses why tests pass inconsistently and suggests fixes for timing, ordering, and state isolation issues.