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ken-chy129

jp-report

by Anygen Selected Skill · GitHub ↗ · v1.0.1 · MIT-0
cross-platform ✓ Security Clean
153
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Install in OpenClaw
/install jp-report
Description
Create formal Japanese corporate HTML and PDF reports from source text for business, compliance, or security documents with structured chapters and professio...
README (SKILL.md)

Generate a formal Japanese corporate document (日本企業向け正式報告書) from the provided source material.

INPUTS

If $ARGUMENTS is provided, treat it as the source file path or inline content. Otherwise, ask the user for:

  1. Source material — file path or pasted content
  2. Document purpose — e.g. security overview / compliance / product explanation
  3. Japanese title + English subtitle
  4. Classification level — 社外秘 / 部外秘 / 社内限り (default: 社外秘)
  5. Output folder path
  6. Revision number (default: Rev. 1.0)

STEP 1 — ANALYZE

Read source material. Identify:

  • Logical sections → map to 4–6 chapters
  • Content types: principles, tables, architecture diagrams, bullet lists
  • Brand names / technical terms to preserve verbatim
  • Content to exclude (confirm with user if unclear)

STEP 2 — TRANSLATE TO FORMAL JAPANESE

Rewrite all content in 書き言葉・敬体:

  • Verb endings: 〜しております / 〜いたします / 〜となっております
  • Full grammatical sentences — no fragment bullets inside tables or definitions
  • Preserve intact: brand names, acronyms (RBAC, TLS, SSO, BYOK), product names
  • Do NOT add certifications (SOC/ISO/GDPR) unless explicitly in source

STEP 3 — PLAN PAGES

Fixed structure:

Page 1  —  表紙 (Cover)   : centered layout, one full A4 page
Page 2  —  目次 (TOC)     : dotted leaders + page numbers, one full A4 page
Page 3+ —  本文 (Body)    : chapters distributed, target one chapter per page

Numbering: 第1章 / 第2章 … (full-width) · Sections: 1.1 / 1.2 … (decimal)

Before writing HTML, calculate content height using the reference in ${CLAUDE_SKILL_DIR}/docs/design-rules.md. Usable area per page ≈ 980px. State the page plan briefly to the user.


STEP 4 — GENERATE HTML

Write a single self-contained .html file using:

  • CSS from ${CLAUDE_SKILL_DIR}/docs/design-rules.md (include verbatim in \x3Cstyle>)
  • Component HTML from ${CLAUDE_SKILL_DIR}/docs/components.md

Every page must follow this shell:

\x3Cdiv class="page">
  \x3Cdiv class="page-body"> \x3C!-- content --> \x3C/div>
  \x3Cdiv class="page-footer">
    \x3Cdiv class="f-l">[Product / Company]\x3C/div>
    \x3Cdiv class="f-c">[Document title] Rev. X.X\x3C/div>
    \x3Cdiv class="f-r">[Classification] | [Page #]\x3C/div>
  \x3C/div>
\x3C/div>

Cover page body must use:

\x3Cdiv class="page-body" style="display:flex;flex-direction:column;align-items:center;justify-content:center;text-align:center;">

STEP 5 — GENERATE PDF

Immediately after writing the HTML, run:

python3 ${CLAUDE_SKILL_DIR}/scripts/generate_pdf.py [absolute path to .html]

The script handles Chrome invocation and URL-encodes the path automatically. Report the output line (bytes + path) on success.


QUALITY CHECKLIST

  • Cover: content vertically + horizontally centered
  • TOC: page numbers match actual layout
  • Every .page div has a .page-footer
  • No bright colors, emoji, or casual language
  • PDF generated successfully (bytes confirmed)
Usage Guidance
This skill appears coherent and limited to generating paginated HTML and producing a PDF via a local headless Chrome call. Before installing, consider: 1) The generate_pdf.py script invokes a hardcoded macOS Chrome binary path (/Applications/Google Chrome.app/Contents/MacOS/Google Chrome) — ensure you are on macOS with Chrome installed at that location or update the script. 2) The script URL-encodes the path using urllib.parse.quote on the entire path (could produce incorrect file:// URLs for some systems); test PDF generation with filenames containing spaces and Japanese characters. 3) The skill uses ${CLAUDE_SKILL_DIR} to read local docs (design-rules.md, components.md) — this is expected but platform-specific. 4) The skill writes .html/.pdf to whatever output folder the user supplies — do not point it at sensitive system directories. 5) No network calls or credentials are requested, so there's no obvious data exfiltration vector in the files provided. If you need to be extra cautious, review or run the generate_pdf.py locally to confirm it behaves as expected before granting it access to production documents.
Capability Analysis
Type: OpenClaw Skill Name: jp-report Version: 1.0.1 The skill is a legitimate tool for generating formal Japanese corporate reports in HTML and PDF formats. It uses a Python script (scripts/generate_pdf.py) to invoke headless Google Chrome for PDF conversion, which is a standard approach for this task. The logic is transparent, well-documented, and lacks any indicators of data exfiltration, persistence, or malicious intent. The instructions in SKILL.md are strictly focused on document structure, translation, and pagination, and do not contain any prompt-injection attempts to subvert the agent's behavior.
Capability Assessment
Purpose & Capability
Name/description (formal Japanese reports -> HTML+PDF) match the included files: docs for CSS/components, example HTML, and a small script to call headless Chrome. The macOS/Chrome requirement declared in README explains the script's hardcoded Chrome path.
Instruction Scope
SKILL.md restricts operations to reading the provided source text (file or pasted content), building HTML using local docs, and invoking the included Python script to produce a PDF. It references ${CLAUDE_SKILL_DIR} (platform-provided skill directory) to embed local files; this variable is not declared in requires.env but is a normal platform runtime variable. No instructions read unrelated system files or contact external endpoints.
Install Mechanism
No install spec (instruction-only skill) and only a tiny Python script is included. Nothing is downloaded or executed from remote URLs. The README's manual symlink installation is benign guidance.
Credentials
The skill declares no required environment variables, no credentials, and reads only user-provided input files and local docs/components for HTML/CSS. There are no secrets or unrelated env vars requested.
Persistence & Privilege
always:false and the skill does not request persistent system privileges or modify other skills. SKILL.md sets disable-model-invocation:true which reduces the skill's ability to autonomously call the model (not a risk).
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install jp-report
  3. After installation, invoke the skill by name or use /jp-report
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.1
- Documentation update only: README.md modified. - No changes to skill logic or functionality. - All behavior and inputs remain unchanged.
v1.0.0
- Initial release of jp-report skill. - Generates formal Japanese corporate HTML and PDF documents from user-provided source material. - Guided process includes structuring input, translation to formal Japanese, planning layout, and rendering with fixed company report style. - Utilizes provided CSS and HTML components; outputs both .html and PDF with strict visual and linguistic standards. - Includes a quality checklist for consistency and correctness.
Metadata
Slug jp-report
Version 1.0.1
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 2
Frequently Asked Questions

What is jp-report?

Create formal Japanese corporate HTML and PDF reports from source text for business, compliance, or security documents with structured chapters and professio... It is an AI Agent Skill for Claude Code / OpenClaw, with 153 downloads so far.

How do I install jp-report?

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

Is jp-report free?

Yes, jp-report is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does jp-report support?

jp-report is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created jp-report?

It is built and maintained by Anygen Selected Skill (@ken-chy129); the current version is v1.0.1.

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