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 adamwang99/NEUTRON-EVO-OS --skill feature_librarygit clone --depth 1 https://github.com/adamwang99/NEUTRON-EVO-OSWrote 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/adamwang99/neutron-evo-os/feature_library)<a href="https://agentmods.dev/skills/adamwang99/neutron-evo-os/feature_library"><img src="https://agentmods.dev/badge/skills/adamwang99/neutron-evo-os/feature_library/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/adamwang99/neutron-evo-os/feature_library"><img src="https://agentmods.dev/badge/skills/adamwang99/neutron-evo-os/feature_library.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 | $0.00002 | $0.00816 |
| Opus 5.5 | $0.00001 | $0.00326 |
| Sonnet 5.5 | $0.00000 | $0.00163 |
| Haiku 4.5 | $0.00000 | $0.00082 |
Grade A, and why
feature_library 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 2mo 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.
How it starts
The opening of the file, as written. The whole thing — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Feature Library Skill — Pattern Router for Backend, API, Auth, and More
Suggests the best architectural patterns and code implementations for a project based on: tech stack, requirements, and detected use cases.
This skill generalizes the ui_library pattern beyond UI — covering:
- 🔐 Authentication & Authorization (JWT, OAuth, RBAC, sessions)
- 🌐 API Design (REST, error handling, rate limiting, versioning)
- 🗄️ Database & ORM (migrations, repository pattern, query optimization)
- ⚡ Real-time & Async (WebSockets, SSE, background jobs)
- 📁 File Handling (upload, validation, S3, CDN)
- 🛡️ Resilience (circuit breaker, retries, graceful degradation)
- 📊 Observability (structured logging, tracing, metrics)
How It Works
When invoked, this skill:
- Loads structured pattern data from
feature_library.json - Detects tech stack and use cases from project context
- Scores each pattern against requirements
- Returns top recommendations with reasoning + install command + code snippet
Usage
route_feature(task, tech_stack, requirements) → {recommended, alternatives, reasoning}
Example:
from skills.core.feature_library.logic import route_feature
result = route_feature(
task="Build a SaaS API with auth, rate limiting, and background jobs",
tech_stack="python",
requirements="FastAPI backend, PostgreSQL, Redis"
)
# Returns: JWT auth, REST API, Celery background jobs, etc.
Categories & Patterns
| Category | Icon | Patterns |
|---|---|---|
| Authentication | 🔐 | JWT, Sessions (Redis), OAuth 2.0, RBAC |
| API Design | 🌐 | REST, Error Handling, Rate Limiting |
| Database | 🗄️ | Migrations (Alembic), Repository Pattern + ORM |
| Real-time | ⚡ | WebSockets, SSE, Background Jobs (Celery) |
| File Handling | 📁 | Secure Upload, Presigned S3 URLs |
| Resilience | 🛡️ | Circuit Breaker, Retry + Backoff |
| Observability | 📊 | Structured Logging, Distributed Tracing |
Decision Logic
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.
- 2mo ago First seen · 112 lines · 2 tokens per session scan A d8860c491316
feature_library is a skill published in the GitHub repository adamwang99/NEUTRON-EVO-OS (20 stars, last pushed 6mo ago), licensed MIT. It adds 2 tokens to every session and 816 once invoked, about $0.0000 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 2026-08-30.
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