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 agentmods add skills/travisun/opptrix/chip-distribution-factornpx skills add Travisun/Opptrix --skill chip-distribution-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/chip-distribution-factor)<a href="https://agentmods.dev/skills/travisun/opptrix/chip-distribution-factor"><img src="https://agentmods.dev/badge/skills/travisun/opptrix/chip-distribution-factor.svg" alt="Measured on agentmods" 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 | $0.00064 | $0.00365 |
| Opus 5 | $0.00032 | $0.00182 |
| Sonnet 5 | $0.00013 | $0.00073 |
| Haiku 4.5 | $0.00006 | $0.00036 |
Grade A, and why
chip-distribution-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 4d 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
筹码分布因子
方法溯源 QuantsPlaybook「筹码因子」。用日频 OHLCV 换手衰减直方图近似筹码；禁止 qlib。
运行
python scripts/chip_distribution_factor.py --input data.json --output result.json
输入：bars 含 open/high/low/close/volume。params.lookback（默认 60）、bins（默认 20）。
输出：signal 按因子降序；有 panels.chip_distribution → full，OHLCV 推演 → proxy。
依赖
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.
- 4d ago First seen · 37 lines · 64 tokens per session scan A 634249df6316
chip-distribution-factor is a skill published in the GitHub repository Travisun/Opptrix (229 stars, last pushed yesterday), licensed Apache-2.0. It adds 64 tokens to every session and 365 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 2026-08-30.
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