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Deposition Question Development

作者 ChipmunkRPA · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install deposition-question-skill
功能描述
Develop deposition question sets from Relativity-exported PDF productions using a user-provided legal theory. Use when tasks involve reviewing opponent-produ...
使用说明 (SKILL.md)

Relativity Deposition Question Builder

Overview

Analyze one or more Relativity-exported PDF productions against a legal theory and generate deposition questions organized by document ID. Each question includes a reason for asking and a document quote that can be used if the witness denies.

Required Behavior

  • Ask for the legal theory first before producing analysis or questions.
  • Ask for PDF path(s) if not already provided.
  • Extract page-level document IDs from the bottom-right area of each page.
  • If two numeric IDs appear in that area, choose the smaller number as the page document ID.
  • Keep quotes verbatim and include source file plus page number for each quote.
  • Group outputs by document ID and place each question under its document ID heading.
  • Under every question, include:
    • Reason why we ask this question
    • Quote from the document to use in deposition in case the opponent party denies

Workflow

  1. Gather inputs.
    • Confirm the user's legal theory.
    • Confirm PDF source path(s).
    • Optionally gather witness name/role and priority topics.
  2. Extract per-page text and document IDs.
    • Run:
      python scripts/extract_relativity_pages.py \
        --input \x3Cpdf-folder-or-file> \
        --recurse \
        --output \x3Crelativity_pages.json>
      
    • Review pages where selected_document_id is null and flag for manual check.
  3. Build a relevance map for the legal theory.
    • For each page, classify relation to theory: supports, undermines, neutral.
    • Focus question drafting on supports pages first, then undermines pages for impeachment.
  4. Draft deposition questions grouped by document ID.
    • Use short, concrete, single-issue questions.
    • Start with authentication/foundation, then admission and contradiction questions.
    • Use direct quotes from page text for denial follow-up.
  5. Return output in required structure.
    • Follow references/deposition_output_template.md.
    • Keep document IDs in ascending numeric order.

Output Rules

  • Do not merge different document IDs into one section.
  • Do not omit Reason or Quote sections under any question.
  • If no reliable quote exists, mark:
    • Quote from the document to use in deposition in case the opponent party denies: [No direct quote located - manual verification required]
  • Prefer quotes that are short, specific, and tied to one factual proposition.

Resources

  • Extraction tool: scripts/extract_relativity_pages.py
  • Output template: references/deposition_output_template.md

Dependencies

Install once if missing:

python -m pip install --user pdfplumber
安全使用建议
This skill appears to do what it says: it runs a local Python script to parse PDFs, extract bottom-right numeric document IDs, and help draft deposition questions with verbatim quotes. Before use: (1) install pdfplumber from a trusted source (pip) and verify your Python environment; (2) run the extraction on a copy of sensitive productions in a secure machine — the script reads PDFs and writes JSON locally but does not send data externally; (3) manually review pages flagged with missing or ambiguous IDs and verify all quoted text before using it in a deposition; (4) avoid uploading privileged documents to untrusted networks or services when using the skill.
功能分析
Type: OpenClaw Skill Name: deposition-question-skill Version: 1.0.0 The skill bundle is a legitimate tool designed for legal professionals to extract text and document IDs from Relativity-exported PDFs to generate deposition questions. The Python script `scripts/extract_relativity_pages.py` uses the well-known `pdfplumber` library to process local files and contains no network activity, obfuscation, or unauthorized data access. The instructions in `SKILL.md` are strictly aligned with the stated purpose and do not contain any prompt-injection attempts or malicious commands.
能力评估
Purpose & Capability
Name/description match the implementation. The included script and SKILL.md are focused on extracting page text/IDs and organizing questions by document ID; nothing requested (no env vars, no unrelated binaries) is out of scope.
Instruction Scope
Runtime instructions are narrowly scoped: prompt for legal theory and PDF paths, run the provided extraction script, classify pages for relevance, and draft questions with quotes. The instructions do not request unrelated files, credentials, or external endpoints.
Install Mechanism
There is no install spec (instruction-only). The only runtime dependency is pdfplumber (installed via pip as described), which is a reasonable, traceable Python library for PDF parsing.
Credentials
The skill requests no environment variables, credentials, or config paths. The script reads local PDF files and writes a JSON output file as expected for this task.
Persistence & Privilege
The skill is not always-enabled and does not request elevated or persistent privileges; it does not modify other skills or system-wide agent settings.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install deposition-question-skill
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /deposition-question-skill 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
relativity-deposition-question-builder 1.0.0 released - Initial public version for generating deposition question sets from Relativity-exported PDFs. - Extracts and selects page-level document IDs from PDFs as per instructions. - Drafts deposition questions by document ID, always including a reason for the question and supporting quote. - Adheres to required output structure and enforces strict completeness for rationale and quoting. - Guides the user through inputs for legal theory and document sources before analysis.
元数据
Slug deposition-question-skill
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Deposition Question Development 是什么?

Develop deposition question sets from Relativity-exported PDF productions using a user-provided legal theory. Use when tasks involve reviewing opponent-produ... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 241 次。

如何安装 Deposition Question Development?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install deposition-question-skill」即可一键安装,无需额外配置。

Deposition Question Development 是免费的吗?

是的,Deposition Question Development 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Deposition Question Development 支持哪些平台?

Deposition Question Development 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Deposition Question Development?

由 ChipmunkRPA(@chipmunkrpa)开发并维护,当前版本 v1.0.0。

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