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HK IPO Review Optimizer

面向港股 IPO 的事后复盘工具：查看和更新决策记录的实际结果与偏差说明，导出审查数据集，并预览、接受或拒绝调参建议；依赖本地 CLI 与数据库文件。

hackstoic
hackstoic
热度 37.80
最近更新 2026-05-11 17:43:48
分类：知识依赖：代码执行 / 读写文件应用场景：财务 / 数据处理 / 工作流

安装技能

复制下面的话术发给你的 Agent，它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill： npx secure-skills-cli add hkipo-review-optimizer
Metadata
name
hkipo-review-optimizer
description
Review past Hong Kong IPO decisions, update actual outcomes, export review datasets, and accept or reject tuning suggestions. Use when the user wants to learn from completed IPO calls and improve later scoring behavior.
version
0.1.0
metadata
{"openclaw":{"emoji":"🔁","requires":{"bins":["uv"],"config":["~/.hkipo-next/data/hkipo.db"]},"install":[{"id":"install-uv-brew","kind":"brew","formula":"uv","bins":["uv"],"label":"Install uv with Homebrew","os":["darwin","linux"]}]}}

HK IPO Review Optimizer

Use this skill for the post-decision feedback loop.

Runtime

This publish bundle includes the required CLI runtime under runtime/hkipo-next.

From the skill folder:

cd <skill_dir>
uv run --directory runtime/hkipo-next hkipo-next ...

By default review history is stored in ~/.hkipo-next/data/hkipo.db.

Workflow

  1. Use review list to find target records.
  2. Use review show before updating a record.
  3. Use review update to add actual results and variance notes.
  4. Use review export when another tool needs a JSON dataset.
  5. Use apply-suggestions show before accepting or rejecting imported suggestions.

Commands

List recent review records:

cd <skill_dir>
uv run --directory runtime/hkipo-next hkipo-next review list --limit 20 --format json

Show a record:

cd <skill_dir>
uv run --directory runtime/hkipo-next hkipo-next review show rvw_123 --format json

Update actual results:

cd <skill_dir>
uv run --directory runtime/hkipo-next hkipo-next review update rvw_123 \
  --allocated-lots 2 \
  --listing-return-pct 14.2 \
  --exit-return-pct 9.8 \
  --realized-pnl-hkd 1860 \
  --notes "Sold into first-day strength" \
  --variance-note "Grey market was weaker than expected but sponsor demand held" \
  --format json

Export a review dataset:

cd <skill_dir>
uv run --directory runtime/hkipo-next hkipo-next review export --from 2026-04-01 --to 2026-04-16 --output /tmp/hkipo-review.json --format text

Preview and accept a suggestion:

cd <skill_dir>
uv run --directory runtime/hkipo-next hkipo-next apply-suggestions show sgg_123 --format json
uv run --directory runtime/hkipo-next hkipo-next apply-suggestions accept sgg_123 --reason "Matches observed listing-day slippage" --format json

Output Cues

  • Review records preserve the original prediction payload, data status, and source issue count.
  • Suggestion detail output shows whether a proposed change would create a new parameter version.

Companion Skills

  • Use $hkipo-parameter-manager when a review conclusion needs manual tuning work.
  • Use $hkipo-decision-engine to rerun fresh decisions after a rule change.