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study

Use when an unfamiliar, costly, or high-risk task needs evidence before a decision or change.

Skill by nmnmcc

IndexedMIT★ 3
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Install

Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/nmnmcc-study

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

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About

Use when an unfamiliar, costly, or high-risk task needs evidence before a decision or change.

Use cases: productivity

No reviews yet. Installed it? Reviews come from verified installers only. How reviews work

Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

Tools
No tools found
Secrets
None asked for
Install scripts
None found

Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/study

What's inside

Skill name
study
Description
Use when an unfamiliar, costly, or high-risk task needs evidence before a decision or change.
License
MIT
Instructions
12 lines in SKILL.md · view on GitHub

Files (3)

  • SKILL.md
  • openai.yaml · agents/
  • guide.md · references/

SKILL.md (first lines)

# Study

Use this skill when the next move depends on an important unknown. Inspect the real artifact and its behavior, then gather only the evidence that can change the decision. Keep study brief for familiar, reversible work.

1. State the requested result and the unknown that could change it.
2. Inspect the closest primary source: code, data, contract, behavior, or user evidence.
3. Compare the strongest plausible alternatives and failure modes.
4. Make the smallest useful probe or change, then use its result as new evidence.

Read [the detailed guide](references/guide.md) when the work is contested, high consequence, or broad enough to need an evidence map. Stop when the decisive facts are supported and remaining uncertainty is explicit.

From nmnmcc/skills, MIT.

More from nmnmcc/skills

Signals

Stars
3
Forks
0
Open issues
0
Last commit (this folder)
Sep 8, 2026 (1 month ago)

From GitHub (fetched Oct 24, 2026).

Details

License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

More from nmnmcc

Cite this page

study skill. Agent Mart. https://agentmart.dev/skills/nmnmcc-study (last updated 2026-10-24)