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 Travisun/Opptrix --skill microstructure-w-factorgit clone --depth 1 https://github.com/Travisun/OpptrixWrote 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/travisun/opptrix/microstructure-w-factor)<a href="https://agentmods.dev/skills/travisun/opptrix/microstructure-w-factor"><img src="https://agentmods.dev/badge/skills/travisun/opptrix/microstructure-w-factor/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/travisun/opptrix/microstructure-w-factor"><img src="https://agentmods.dev/badge/skills/travisun/opptrix/microstructure-w-factor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- 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 | $0.00061 | $0.00353 |
| Opus 5 | $0.00030 | $0.00177 |
| Sonnet 5 | $0.00012 | $0.00071 |
| Haiku 4.5 | $0.00006 | $0.00035 |
Grade A, and why
microstructure-w-factor 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 5d 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
反转微观 W 因子（日频规则版）
方法溯源开源证券「A股反转之力的微观来源」。完整高频路径降级为日频：
overnight = open_t / close_{t-1} − 1，day = close_t / open_t − 1，
W ≈ mean(overnight − day) 窗口版（隔夜相对日间的反转结构代理）。
运行
python scripts/microstructure_w_factor.py --input data.json --output result.json
默认 create_web。仅标准库。
What ships with it
2 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.
- 5d ago First seen · 35 lines · 61 tokens per session scan A 9266969b369c
microstructure-w-factor is a skill published in the GitHub repository Travisun/Opptrix (231 stars, last pushed yesterday), licensed Apache-2.0. It adds 61 tokens to every session and 353 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.
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