Insight Claw

Insight Claw 是面向 A 股自选股的自动化自选股分析流水线。它围绕一组自选股收集行情数据、筹码分布和搜索情报，调用模型生成结构化分析，最终产出可保存或推送的决策结果。

When to Use

Use this skill when a user wants OpenClaw or Hermes to download, configure, run, verify, or troubleshoot Insight Claw.

Host Compatibility

This is a shell-based skill for agent hosts that can run local commands. It follows the same operational path in OpenClaw and Hermes:

1. Reuse an existing Insight Claw checkout when one is present.
2. Clone https://github.com/GeraltJc/insight-claw only for first-time setup.
3. Create or reuse .venv.
4. Run the local JusticePlutus CLI with a temporary --stocks self-selected stock override.

Use OpenClaw for ClawHub installation and updates. Use Hermes when the user has already installed this skill in a Hermes skill path. Do not mix host-specific install flows in one turn; pick the host the user is actually using, then run the same local validation command.

Quick Reference

Insight Claw is an A-share self-selected stock analysis pipeline.

For expanded commands, environment examples, GitHub Actions setup, and troubleshooting details, read:

• references/quickstart.md
• references/troubleshooting.md

If the user is already inside an Insight Claw checkout, reuse it instead of cloning a duplicate repository.

OpenClaw Installation

After this skill is published on ClawHub, OpenClaw users can install it from the registry:

openclaw skills search insight-claw
openclaw skills install insight-claw

For local development before publication, point OpenClaw at this folder or copy the folder into the active OpenClaw skills directory. The skill bundle is this directory only: SKILL.md plus references/.

OpenClaw metadata lives under metadata.openclaw. Optional provider keys are declared with envVars instead of requires.env because Insight Claw can run with either AIHUBMIX_KEY or OPENAI_API_KEY, and search, chip distribution, 同花顺专业数据模式, and notifications are enhancement paths rather than mandatory setup.

Execution Contract

OpenClaw and Hermes should not clone and reinstall on every request. Use this decision flow:

First-time setup

Run these commands only when the Insight Claw repository or .venv environment is missing:

git clone https://github.com/GeraltJc/insight-claw.git insight-claw
cd insight-claw
python -m venv .venv
.venv/bin/python -m pip install -r requirements.txt
.venv/bin/python -m justice_plutus run --stocks 000001,600519 --workers 1 --no-notify

Subsequent runs

When the repository and .venv already exist, run only the analysis command:

cd insight-claw
.venv/bin/python -m justice_plutus run --stocks 000001,600519 --workers 1 --no-notify

Reinstall dependencies only after project updates, requirements.txt changes, or virtual environment failure.

Runtime Requirements

Before running Insight Claw, confirm these requirements:

• Python 3.11+
• git
• pip
• venv
• Network access for dependency installation and configured data, search, LLM, or notification providers.
• At least one LLM key for real structured analysis. Prefer AIHUBMIX_KEY; use OPENAI_API_KEY as fallback or primary key when appropriate.

Procedure

Follow the common local setup path first.

1. Locate an existing checkout by looking for justice_plutus/, src/, and requirements.txt in the working tree.
2. If no checkout exists, ask where the user wants the project stored, then download it from https://github.com/GeraltJc/insight-claw with git clone.
3. Change into the repository directory.
4. Create an isolated Python environment with python -m venv .venv.
5. Install dependencies with pip install -r requirements.txt from inside the isolated environment.
6. Configure at least one LLM key path before a real analysis run. Prefer AIHUBMIX_KEY with OpenAI-compatible settings, or use OPENAI_API_KEY as fallback.
7. Run the first validation without notifications:

.venv/bin/python -m justice_plutus run --stocks 000001,600519 --workers 1 --no-notify

Equivalent command after activating the virtual environment:

python -m justice_plutus run --stocks 000001,600519 --workers 1 --no-notify

Use --stocks for a temporary self-selected stock override. It does not mutate the persistent STOCK_LIST configuration.

Configuration

Keep configuration layered so the first run stays small:

Use project terms consistently when explaining results:

• 行情数据: historical daily bars and real-time quote facts.
• 搜索情报: open search context used to enrich model input.
• 结构化分析: model output in a parseable decision schema.
• 决策结果: user-facing conclusion, risk, and action context.
• 分析报告: local persisted report files.
• 批次汇总: overview across all self-selected stocks in one run.
• 通知消息: Telegram, Feishu, or another outbound message shape.
• 降级链: the ordered fallback behavior for data sources, model routes, and notification outputs.

Verification

Confirm that a no-notification validation run completes and produces reports:

• reports/YYYY-MM-DD/stocks/\x3Ccode>.md
• reports/YYYY-MM-DD/stocks/\x3Ccode>.json
• reports/YYYY-MM-DD/summary.md
• reports/YYYY-MM-DD/summary.json
• reports/YYYY-MM-DD/run_meta.json

GitHub Actions

Use GitHub Actions only after the local flow is understood.

1. Configure GitHub Actions Secrets for secret values such as AIHUBMIX_KEY, OPENAI_API_KEY, BOCHA_API_KEYS, TAVILY_API_KEYS, SERPAPI_API_KEYS, TUSHARE_TOKEN, TELEGRAM_BOT_TOKEN, and optional provider tokens.
2. Configure GitHub Actions Variables for non-secret values such as STOCK_LIST, OPENAI_BASE_URL, OPENAI_MODEL, MAX_WORKERS, REPORT_TYPE, and TELEGRAM_CHAT_ID if the repository treats that chat id as non-secret.
3. Trigger .github/workflows/justice_plutus_analysis.yml with workflow_dispatch.
4. Use the workflow_dispatch.stocks input for a temporary self-selected stock override. This should not change the persistent STOCK_LIST variable.
5. Inspect the run status, generated artifacts, and notification channel separately. A notification failure does not necessarily mean analysis reports were not generated.

Pitfalls

• Missing LLM keys block real structured analysis. Ask the user to configure a key securely; do not print raw secret values back to the conversation.
• Missing search, chip distribution, or 同花顺专业数据模式 credentials should be explained as optional enhancement gaps when the core run can still proceed.
• Data-source failures may be normal degradation chain behavior. Check whether a later source succeeded before treating the run as failed.
• Notification failures should be isolated from report generation. Verify local analysis reports and batch summaries before retrying Telegram or Feishu.
• Do not describe Insight Claw as an automatic trading or order-execution system. It produces decision results for user review.

Publishing

This skill is intended for public OpenClaw/ClawHub and Hermes distribution. Keep the bundle small: SKILL.md plus optional text references or small helper scripts only when they remove real repeated work.

To publish to ClawHub:

clawhub login
clawhub skill publish skills/hermes/insight-claw --slug insight-claw --name "Insight Claw" --version 0.2.0 --changelog "Add OpenClaw and ClawHub compatibility metadata while preserving Hermes usage."

ClawHub skill publications are distributed under MIT-0. Do not add conflicting license terms to this skill bundle.

To publish to a Skills Hub:

hermes skills publish skills/hermes/insight-claw --to github --repo GeraltJc/insight-claw

To expose the repository as a custom tap:

hermes skills tap add GeraltJc/insight-claw

Before publishing, review the bundle as a community skill that will pass the ClawHub and Hermes security scanners:

• Data exfiltration: do not upload reports, .env files, or generated artifacts without explicit user approval.
• Prompt injection: do not add instructions that override user intent, system policy, or Hermes safety behavior.
• Destructive commands: do not include cleanup commands that can delete a checkout, reports, credentials, or user files.
• Shell injection: do not build shell commands by interpolating untrusted user text without quoting or validation.