Skip to content
Back to skills

Case Study Writer

ASecurity

Write public-safe case studies from private projects, automations, agent workflows, internal tools, demos, or client-facing systems. Use when the user asks to turn project work into a case study, create client proof, write a sanitized GitHub case study, summarize an internal system publicly, document an automation without sharing source code, or explain a workflow while removing credentials, raw prompts, logs, databases, client data, local paths, and private implementation details.

  • 3 stars
  • 0 votes
  • 0 copies
  • 1 view
  • Added October 15, 2026
ai-agentspythongosqlgitapidatabase

Works with

  • cli
  • api

Security analysis

A100/100

Pro scans all 4 files and shows the line behind each finding

Scanned October 15, 2026

npx -y skills add jqaisystems/jqai-ai-skills --skill case-study-writer --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Case Study Writer?

Add the live security badge to your README. It updates with every re-scan.

Security grade badge for Case Study Writer
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/jqaisystems-case-study-writer/badge)](https://www.skillsdirectory.com/skills/jqaisystems-case-study-writer)

More formats (shields.io, HTML) on the badges page. Keep it an A: scan every change in CI with Pro.

Download with Pro
SKILL.md
---
name: case-study-writer
description: Write public-safe case studies from private projects, automations, agent workflows, internal tools, demos, or client-facing systems. Use when the user asks to turn project work into a case study, create client proof, write a sanitized GitHub case study, summarize an internal system publicly, document an automation without sharing source code, or explain a workflow while removing credentials, raw prompts, logs, databases, client data, local paths, and private implementation details.
---

# Case Study Writer

## Overview

Use this skill to turn private project work into public-safe proof: concise case studies that explain the problem, workflow, outcome, and adaptation value without exposing source code, credentials, raw prompts, logs, databases, client data, or private implementation details.

## Workflow

1. Clarify the public artifact target: GitHub case study, website system page, portfolio note, demo companion, or README section.
2. Read `references/case-study-template.md` and use its section order unless the destination already has a stronger house style.
3. Read `references/safety-boundary-examples.md` before writing the opening boundary note and final Safety Boundary section.
4. Extract only public-safe facts:
   - Problem the system solves.
   - What the system does at workflow level.
   - Human review and approval points.
   - General stack categories when useful.
   - Outcome stated qualitatively or with approved aggregate numbers.
   - What a similar client could adapt.
5. Rewrite private details into generic, reusable language. Do not copy raw notes, prompts, logs, exports, database rows, or source code.
6. Produce the case study in Markdown and include a short safety verdict: `BLOCK`, `REVIEW`, or `READY`.

## Case Study Shape

Use these sections by default:

- Title
- Boundary note
- Public page or demo links, if already approved and live
- Problem
- What The System Does
- Workflow
- Outcome
- What Can Be Adapted For Clients
- Safety Boundary

Keep the case study short enough to scan quickly. Prefer six to eight workflow steps and three to five client-adaptation bullets.

## Safety Rules

- Never include source code, private prompts, API keys, credentials, databases, logs, exports, client messages, account identifiers, local paths, or screenshots with private UI.
- Do not name clients, prospects, internal codenames, domains, or people unless the user confirms they are approved for public use.
- Use broad stack categories such as Python, SQLite, browser automation, queue dashboard, or LLM API instead of exact private architecture when details are not needed.
- Mention human approval explicitly when the system drafts, scores, publishes, sends, spends, or changes a system of record.
- If the user provides risky source material, return `BLOCK` with removal instructions before writing the publishable draft.

## Output Format

Return:

1. Safety verdict: `BLOCK`, `REVIEW`, or `READY`.
2. Short note on what was excluded or generalized.
3. The Markdown case study.
4. Remaining checks before publication.

If the user asks you to edit files, write the draft into the requested location or a sanitized staging folder, then recommend running a public-safety scan before commit.

Files in this skill

  • SKILL.md3.2 KB
  • agents/openai.yaml223 B
  • references/case-study-template.md1.7 KB
  • references/safety-boundary-examples.md1.9 KB

Attribution

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments

Loading comments…

Newsletter

Get the weekly list of safe new skills, and the ones we pulled.