Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add scoobynko/case-study-skill --skill case-studygit clone --depth 1 https://github.com/scoobynko/case-study-skillWrote 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/scoobynko/case-study-skill/case-study)<a href="https://agentmods.dev/skills/scoobynko/case-study-skill/case-study"><img src="https://agentmods.dev/badge/skills/scoobynko/case-study-skill/case-study/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/scoobynko/case-study-skill/case-study"><img src="https://agentmods.dev/badge/skills/scoobynko/case-study-skill/case-study.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00161 | $0.07178 |
| Opus 5.5 | $0.00064 | $0.02871 |
| Sonnet 5.5 | $0.00032 | $0.01436 |
| Haiku 4.5 | $0.00016 | $0.00718 |
Grade A, and why
case-study 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 1mo 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 — 400 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Case Study Skill
Help designers present their work and their way of working. Outputs a single .md file with screenshot placeholders and capture instructions.
A good case study is not a job application. It is a window into how someone thinks, makes decisions, and relates to craft. When a case study does that well, hiring takes care of itself.
This skill has two modes, detected automatically from the user's prompt:
- Designer mode: the user describes a project, uploads Figma screens, or talks about work they did. The agent coaches them through the right questions and structures the narrative.
- Design engineer mode: the user provides a git branch, diff, or PR. The agent reads the code changes, asks context questions, discovers metrics via analytics MCP if available, and writes the case study grounded in what actually shipped.
The agent always asks questions first. It never fills sections with assumptions.
Hard rule: no answer, no section. If the user did not provide an answer to the question that backs a section, that section does not appear in the draft. The agent never invents trade-offs, "what I'd do differently," lessons learned, rejected approaches, point-of-view statements, craft details, metrics, or any other content the user has not supplied or confirmed. If a section feels important and the user has not answered, ask the question. If the user declines or skips, leave the section out — do not fill it with plausible-sounding content. Hallucinating any part of a case study is the worst possible failure mode of this skill.
Philosophy
Core principles:
- Be a coach, not a template. Ask questions, challenge weak answers, suggest what's missing. Don't fill in blanks with generic text.
- Show the thinking, not just the result. The work itself is half the case study. The other half is how the designer got there, what they believed, what they struggled with, and what they learned.
- Find the interesting part and build around it. Not every project has the same story shape. Some are about a hard design decision. Some are about craft. Some are about navigating ambiguity. Structure the case study around what makes this project worth reading about.
- Specific beats vague. "Checkout abandonment dropped from 67% to 41%" beats "significantly improved conversion." "
translateY(-2px)on hover with 120ms ease-out" beats "improved micro-interactions." - Honest beats impressive. Show rejected directions. Admit trade-offs. Say "this didn't ship" if it didn't. Skip sections that would be filler.
- Short. Target 800 to 1,500 words. 5 to 8 minute read.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 400 lines · 161 tokens per session scan A 7a2761217727
case-study is a skill published in the GitHub repository scoobynko/case-study-skill (11 stars, last pushed 18d ago), licensed MIT. It adds 161 tokens to every session and 7,178 once invoked, about $0.0006 per session on Opus 5.5. 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 2026-08-31.
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