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 agentpit-io/hunter-community --skill investor_panelgit clone --depth 1 https://github.com/agentpit-io/hunter-communityWrote 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/agentpit-io/hunter-community/investor_panel)<a href="https://agentmods.dev/skills/agentpit-io/hunter-community/investor_panel"><img src="https://agentmods.dev/badge/skills/agentpit-io/hunter-community/investor_panel/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/agentpit-io/hunter-community/investor_panel"><img src="https://agentmods.dev/badge/skills/agentpit-io/hunter-community/investor_panel.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 | $0.00038 | $0.01054 |
| Opus 5 | $0.00019 | $0.00527 |
| Sonnet 5 | $0.00008 | $0.00211 |
| Haiku 4.5 | $0.00004 | $0.00105 |
Grade A, and why
investor_panel 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
Investor Panel · 大佬评审团（Hunter 适配版）
66 位投资者分成 9 个流派，各自用自己的方法论对同一只股票投票。 这个 SKILL 的价值不在于给出结论，而在于把分歧摆出来 —— 让用户看清同一份数据在不同框架下能读出完全相反的意思。
执行流程
1. 取数
调 uzi_stock_deep_analysis 拿这只股票的真实数据（行情 / K 线 / 财务 /
公告 / 新闻等）。
⚠️ outline 参数只传数据类小节，或者干脆不传。
后端手里只有上面那几段数据，它写不出「投票分布」，也不知道芒格会怎么说；
把角色类小节塞进 outline，它只会写一句「暂无数据」。
66 位大佬的戏份全部在你的正文里完成。
2. 投票
按 references/voting-rules.md 的规则推导 —— 不是拍脑袋编比例：
- 每个流派有一张打分维度表，逐维对照真实数据打 -2 到 +2 分
- 分数和 ≥ +3 投牛、-2~+2 投中性、≤ -3 投熊
- 数据缺失的维度记 0 分；一个流派过半维度缺数据，该流派全部记中性
- 综合评分 = 50 + (牛票 - 熊票) / 66 × 50
3. 发言
9 个流派的方法论与成员名单：
references/group-a-classic-value.md· 经典价值（8 席）references/group-b-quality-growth.md· 质量成长（8 席）references/group-c-disruptive-tech.md· 颠覆式创新（8 席）references/group-d-macro-cycle.md· 宏观与周期（8 席）references/group-e-trend-momentum.md· 趋势与动量（8 席）references/group-f-hot-money.md· 游资与情绪（8 席）references/group-g-quant-systematic.md· 量化与系统化（7 席）references/group-h-contrarian-short.md· 逆向与做空（6 席）references/group-i-tail-risk.md· 尾部风险与对冲（5 席）
每个流派文件末尾都有发言模板：先引真实数字，再下判断。
输出格式
- 一句话结论 —— 分歧点在哪
- 投票分布 —— 牛 / 中性 / 熊 票数与比例、综合评分与档位
- 分流派详述 —— 9 个流派每个都要写到：席位数、态度、打分依据 （引用真实数字）、1-2 位代表人物的第一人称点评
- 最大分歧 —— 哪两派结论相反，各自依据是什么
- 跟踪清单 —— 什么数据出来能让分歧收敛
第 3 部分是主体。不要只挑两三个流派说完就收尾 —— 用户点这个 SKILL 就是为了看 66 个人怎么吵起来的。
硬约束
- 所有数字来自工具返回的数据，一个都不许编。没有的就说没有。
- 人物观点标注是模拟：写「模拟巴菲特的方法论推演」，不要写成 「巴菲特说」。这是按公开方法论做的角色推演，不是本人言论， 也不代表他们的真实持仓或表态。
- 不给买卖评级、目标价、仓位建议。 综合评分是分歧度指标，不是推荐等级。
- 全程中文，英文只用于股票代码和 ROE / EPS / PEG 这类缩写。
What ships with it
10 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.
- references/group-a-classic-value.md 2.3 KB
- references/group-b-quality-growth.md 2.0 KB
- references/group-c-disruptive-tech.md 2.2 KB
- references/group-d-macro-cycle.md 2.0 KB
- references/group-e-trend-momentum.md 2.1 KB
- references/group-f-hot-money.md 2.1 KB
- references/group-g-quant-systematic.md 1.9 KB
- references/group-h-contrarian-short.md 1.9 KB
- references/group-i-tail-risk.md 1.7 KB
- references/voting-rules.md 3.6 KB
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 Changed · +52 lines · +1 tokens per session 3489e4341b23
- 11d ago First seen · 29 lines · 37 tokens per session scan A 4c2339734546
investor_panel is a skill published in the GitHub repository agentpit-io/hunter-community (506 stars, last pushed yesterday), licensed Apache-2.0. It adds 38 tokens to every session and 1,054 once invoked, about $0.0002 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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