Nexent is a zero-code platform for creating AI agents from natural-language instructions, combining tools, skills, memory, orchestration, constraints, feedback loops, and control planes. It is intended for people who need to build and deploy agents without writing orchestration code. The catalogue entries are rules and skills for working with Nexent.
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 ModelEngine-Group/nexent --skill skillgit clone --depth 1 https://github.com/ModelEngine-Group/nexentWrote 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/modelengine-group/nexent/skill)<a href="https://agentmods.dev/skills/modelengine-group/nexent/skill"><img src="https://agentmods.dev/badge/skills/modelengine-group/nexent/skill/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/modelengine-group/nexent/skill"><img src="https://agentmods.dev/badge/skills/modelengine-group/nexent/skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00015 | $0.00089 |
| Opus 5.5 | $0.00006 | $0.00036 |
| Sonnet 5.5 | $0.00003 | $0.00018 |
| Haiku 4.5 | $0.00002 | $0.00009 |
Grade A, and why
tfp-verification 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 3d 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.
What it actually says
Use read_skill_config to retrieve this Agent's marker and numeric value.
The verification script is scripts/report.py. It accepts --nonce and
--value, writes one UTF-8 report in the execution output directory, and
prints its relative filename. Use upload_to_s3 to publish that report.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 3d ago First seen · 10 lines · 15 tokens per session scan A dedfb40e6017
tfp-verification is a skill published in the GitHub repository ModelEngine-Group/nexent (5,955 stars, last pushed today), licensed MIT. It adds 15 tokens to every session and 89 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-10-14.
Other skills, from other repositories
rn-testing
This skill should be used when the user asks to "write a Maestro test", "create E2E flows", "add testIDs", "run UI tests", "run E2E tests", "verify a feature works", "test my screen", "set up maestro-runner", "mock network requests", "inspect store state", "write test assertions", or needs guidance on test timing…
capturing-proof
This skill should be used when the user asks to "capture proof", "record a demo of this feature", "make a video showing it works", "record the flow for the PR", "generate a PR body", "capture screenshots for the PR", "proof-capture", or when a verified feature needs PR-ready proof artifacts (video + numbered…
run-action
Explicit Codex workflow: Execute a learned Maestro flow ("action") by name with optional -e KEY=VALUE parameters. Looks the flow up via packages/rn-dev-agent-core/dist/learned-actions.js (same inventory as $rn-dev-agent:list-learned-actions), then replays it via cdprunaction — auto-repair-aware orchestration with…
build-and-test
Explicit Codex workflow: Build the Expo/React Native app (local or EAS), install it, start Metro, then test a requested feature end-to-end.
test-generation-patterns
Use this skill when generating tests with AI assistance. Activate when the user wants to create unit tests, integration tests, generate test cases, improve test coverage, write tests for existing code, or set up testing patterns for their project.
playwright-patterns
Write reliable, maintainable E2E tests with Playwright best practices. Use this skill when writing Playwright tests, debugging flaky tests, or setting up E2E automation. Activate when: playwright, e2e test, end-to-end, browser testing, UI automation, web testing.