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hackstoic

HK IPO Review Optimizer

by hackstoic · GitHub ↗ · v0.1.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install 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 lear...
README (SKILL.md)

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 \x3Cskill_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 \x3Cskill_dir>
uv run --directory runtime/hkipo-next hkipo-next review list --limit 20 --format json

Show a record:

cd \x3Cskill_dir>
uv run --directory runtime/hkipo-next hkipo-next review show rvw_123 --format json

Update actual results:

cd \x3Cskill_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 \x3Cskill_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 \x3Cskill_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.
Usage Guidance
This skill bundles an entire CLI runtime and will: (1) write/read a local sqlite DB at ~/.hkipo-next/data/hkipo.db, and (2) make outbound HTTP requests to multiple public IPO data sources (AAStocks, AiPO, HKEX, Tencent APIs, etc.). No credentials are requested, which is proportionate, but you should: verify the skill's source/author (no homepage/source provided), inspect the bundled runtime if you can, and confirm the Homebrew 'uv' formula provenance before installing. If you are cautious, run it in an isolated environment (container or VM), back up or sandbox ~/.hkipo-next/data/hkipo.db, and monitor outbound network connections during first runs.
Capability Analysis
Type: OpenClaw Skill Name: hkipo-review-optimizer Version: 0.1.0 The hkipo-review-optimizer skill is a legitimate tool designed for analyzing Hong Kong IPO data and tracking investment decisions. It fetches financial data from public sources such as HKEX, AAStocks, and Jisilu, and manages a local SQLite database (~/.hkipo-next/data/hkipo.db) to store review history and scoring parameters. The codebase is well-structured, utilizing Pydantic for data validation and standard libraries for networking and storage, with no evidence of data exfiltration, malicious execution, or harmful prompt injection instructions.
Capability Assessment
✓ Purpose & Capability
Name/description (post-decision IPO review, export datasets, accept/reject suggestions) align with the declared requirements: it needs a CLI runner ('uv') and a local DB (~/.hkipo-next/data/hkipo.db) to store review history. The bundled code implements data fetchers, exporters, and review/apply-suggestion commands that match the described functionality.
ℹ Instruction Scope
SKILL.md instructs the agent to run the included CLI (uv run --directory runtime/hkipo-next hkipo-next ...). That runtime reads/writes the configured DB path and makes outbound HTTP(S) requests to public data sources (aipo.myiqdii.com, aastocks.com, hkex, Tencent APIs, etc.). This network activity is expected for the stated purpose, but users should be aware the skill will perform external requests and parse tokens/pages as part of normal operation.
ℹ Install Mechanism
Install spec is a single Homebrew formula 'uv' that creates a 'uv' binary; this is proportional to the runtime instructions which expect 'uv'. Homebrew is a standard distribution channel, but you should verify which 'uv' formula is being installed (provenance) before proceeding.
✓ Credentials
The skill declares no environment variables or secrets and lists only a single config path (~/.hkipo-next/data/hkipo.db). The code does not require unrelated credentials. Network calls are made to public data sources (no embedded secret exfiltration fields).
✓ Persistence & Privilege
always:false and user-invocable: true. The skill stores review history in its own DB path under the user's home directory and does not request elevated or cross-skill privileges. It does not modify other skills' configs according to the bundle.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install hkipo-review-optimizer
  3. After installation, invoke the skill by name or use /hkipo-review-optimizer
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v0.1.0
Initial ClawHub release
Metadata
Slug hkipo-review-optimizer
Version 0.1.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is HK IPO Review Optimizer?

Review past Hong Kong IPO decisions, update actual outcomes, export review datasets, and accept or reject tuning suggestions. Use when the user wants to lear... It is an AI Agent Skill for Claude Code / OpenClaw, with 76 downloads so far.

How do I install HK IPO Review Optimizer?

Run "/install hkipo-review-optimizer" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is HK IPO Review Optimizer free?

Yes, HK IPO Review Optimizer is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does HK IPO Review Optimizer support?

HK IPO Review Optimizer is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created HK IPO Review Optimizer?

It is built and maintained by hackstoic (@hackstoic); the current version is v0.1.0.

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