Borrowing it
Nothing to install: this file belongs to EthanAlgoX/LLM-TradeBot. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/EthanAlgoX/LLM-TradeBot/main/.claude/skills/analyze-pr/SKILL.mdgit clone --depth 1 https://github.com/EthanAlgoX/LLM-TradeBotWrote 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/ethanalgox/llm-tradebot/analyze-pr)<a href="https://agentmods.dev/skills/ethanalgox/llm-tradebot/analyze-pr"><img src="https://agentmods.dev/badge/skills/ethanalgox/llm-tradebot/analyze-pr.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 145 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00000 | $0.01517 |
| Opus 5 | $0.00000 | $0.00758 |
| Sonnet 5 | $0.00000 | $0.00303 |
| Haiku 4.5 | $0.00000 | $0.00152 |
Grade A, and why
analyze-pr 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 8d 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.
How it starts
The opening of the file, as written. The whole thing — 162 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Analyze PR
分析 GitHub Pull Request，评估必要性、描述完整性、验证证据、主要风险与是否可直接合入。
Repository: https://github.com/ZhuLinsen/daily_stock_analysis/pulls
Usage
/analyze-pr <pr_number>
Instructions
分析时使用简洁中文，优先遵循仓库根目录 AGENTS.md 和 .github/PULL_REQUEST_TEMPLATE.md。
Step 1: 同步最新代码基线
分析 PR 前必须先刷新远端状态，并尽量把本地安全推进到最新基线：
git status --short
git fetch --all --prune
# 仅当工作区干净且当前分支可 fast-forward 时执行：
git pull --ff-only
- 只有在工作区干净、当前分支有可 fast-forward 的上游时，才执行并接受
git pull --ff-only的结果。 - 如存在本地改动、冲突状态、未跟踪风险文件、无上游分支或无法 fast-forward，不要执行
stash、reset、强制切分支或覆盖本地状态；改用已 fetch 的origin/main、PR head 或 GitHub diff 做分析。 - 在输出文档的
Validation Evidence中记录同步结果：本地 HEAD、使用的远端基线，以及未更新本地工作树的原因（如有）。
Step 2: 拉取 PR 基本信息
gh pr view <pr_number> --repo ZhuLinsen/daily_stock_analysis
gh pr view <pr_number> --repo ZhuLinsen/daily_stock_analysis --comments
gh pr checks <pr_number> --repo ZhuLinsen/daily_stock_analysis
gh pr diff <pr_number> --repo ZhuLinsen/daily_stock_analysis
如有失败的 CI，优先查看失败日志，而不是立刻在本地重跑全部检查：
gh run view <run_id> --log-failed
Step 3: 检查标题与描述完整性
先检查 PR title 是否符合 AGENTS.md 的非阻断建议：
- 格式应为
<类型>: <修改内容>，例如fix: 修复大盘分析历史记录丢失 - 类型优先为
fix/feat/refactor/docs/chore/test/ci - 不应包含
[codex]、codex、autocode、copilot或其他工具/agent 来源前缀 - 标题应描述实际变更；若标题与 diff 不符，在描述完整性中指出，但不应单独作为 review process blocker。
对照 .github/PULL_REQUEST_TEMPLATE.md，确认是否覆盖：
PR TypeBackground And ProblemScope Of ChangeIssue LinkVerification Commands And ResultsVisual Evidence（仅当 PR 修改报告格式、报告渲染效果或 Web UI 界面时要求截图或替代可视证据）Compatibility And RiskRollback Plan
若 PR 涉及第三方模型 / API 兼容语义、请求参数固定值、OpenAI-compatible 路由、YAML alias、fallback 行为或运行时配置保存 / 清理 / 迁移逻辑，还要额外检查描述里是否明确写出：
- 官方来源链接或公告
- 当前锁定依赖 / 运行时兼容范围（例如 LiteLLM 版本窗口）
- 已验证的调用链路覆盖面
- 旧配置是否会被静默改写、清空、迁移或保持不变
- 最小回滚路径（通常是 revert 本 PR）
若 PR 修改报告格式、报告渲染效果或 Web UI 界面，还要检查 Visual Evidence 是否附受影响报告 / 页面截图；涉及前后差异时优先检查前后对比。若无法截图，描述中应说明原因与替代可视证据。
Step 4: 优先使用 CI / Diff 证据
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.
- 8d ago First seen · 162 lines · 0 tokens per session scan A af39a1ac6e4e
analyze-pr is a skill published in the GitHub repository EthanAlgoX/LLM-TradeBot (316 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,517 tokens. 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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