gpt
- Repo stars 330
- License MIT
- Author updated Live
- Author repo claude-skill-registry
- Domain
- Data
- Compatible agents
-
- Claude Code
- Cursor
- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- Trust score
- 94 / 100 · audit passed
- Author / version / license
- @majiayu000 · MIT
- Token usage
- Lean
- Setup complexity
- Plug-and-play
- External API key
- Not required
- Operating systems
- Unspecified (assume cross-platform)
- Runtime requirements
- No special requirements
- Permissions
-
- Read-only
- Write / modify
- Network behavior
- Local-only
- Install commands
- 26 variants
Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.
Heads up: 未限定 allowed-tools,默认拥有全部工具权限。
---
name: gpt
description: Use GPT-5.2 for long-running coding tasks: large refactors, feature implementation etc. Long-con…
category: data
runtime: no special runtime
---
# gpt output preview
## PART A: Task fit
- Use case: Use GPT-5.2 for long-running coding tasks: large refactors, feature implementation etc. Long-context coding. Best for: large refactors, feature implementation. GPT strictly follows instructions. Provide as much high-level design context as possible: runs entirely locally. Works with Claude Code, Cursor, Cline and 23 more..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “Prompt Guidelines / Create Session (with worktree for code edits) / Create Session (read-only, no worktree)” and do not present inference as author intent.
## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “Use GPT-5.2 for long-running coding tasks: large refactors, feature implementation etc. Long-context coding. Best for: large refactors, feature implementation. GPT strictly follows instructions. Provide as much high-level design context as possible: runs entirely locally. Works with Claude Code, Cursor, Cline and 23 more.”.
- **02** When the source has headings, the agent prioritizes “Prompt Guidelines / Create Session (with worktree for code edits) / Create Session (read-only, no worktree)” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, write/modify files; mostly runs locally; usually needs no extra API key.
## Running Rules
- read files, write/modify files; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options. The source mentions slash commands such as `/path`; use them first when your agent supports command triggers.
Name target files or source material, expected output, forbidden changes, and whether network or shell access is allowed. Permission fingerprint: read files, write/modify files.
Start with a small task and check whether the result follows “Prompt Guidelines / Create Session (with worktree for code edits) / Create Session (read-only, no worktree)”. Inspect diffs, logs, previews, or tests before expanding scope.
Confirm the final output includes a concrete result, evidence, and next action. If it stays generic, tighten inputs, boundaries, and acceptance criteria.
---
name: gpt
description: Use GPT-5.2 for long-running coding tasks: large refactors, feature implementation etc. Long-con…
category: data
source: majiayu000/claude-skill-registry
---
# gpt
## When to use
- Use GPT-5.2 for long-running coding tasks: large refactors, feature implementation etc. Long-context coding. Best for:…
- Use it when the task has clear inputs, repeatable steps, and validation criteria.
## What to provide
- Target material, scope, expected result, and forbidden changes.
- Whether network, commands, file writes, or external services are allowed.
## Execution rules
- Organize steps around “Prompt Guidelines / Create Session (with worktree for code edits) / Create Session (read-only, no worktree)” and keep inference separate from source facts.
- read files, write/modify files; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding the task.
## Output requirements
- Return the deliverable, key evidence, validation method, and next action.
- Mark missing information as unknown; do not invent commands, platforms, or dependencies. The author source anchors workflow facts; repository files anchor sources and commands; Fluxly only adds fit, limitations, and quality judgment.
skill "gpt" {
input -> user goal + target files + boundaries + acceptance criteria
context -> Prompt Guidelines / Create Session (with worktree for code edits) / Create Session (read-only, no worktree)
rules -> SKILL.md triggers / order / output contract
runtime -> no special runtime | read files, write/modify files | mostly runs locally
guardrails -> usually needs no extra API key + small-sample validation + diff/log review
output -> copyable result + checklist + next iteration
} GPT-5.2 (via ocw)
Long-context coding. Best for: large refactors, feature implementation.
Prompt Guidelines
GPT strictly follows instructions. Provide as much high-level design context as possible:
- Architecture decisions, data flow, component responsibilities
- Constraints, edge cases, expected behaviors
Avoid:
- Contradictory requirements (GPT will struggle to reconcile conflicts)
- Code snippets — GPT writes code well on its own; use tokens for design info instead
Create Session (with worktree for code edits)
ocw new gpt --worktree
Returns:
- Line 1: 6-char hash
- Line 2: worktree path (e.g.,
/path/to/ocw-abc123)
The worktree is an isolated git branch. Work there freely.
Create Session (read-only, no worktree)
ocw new gpt
Chat
ocw chat <hash> << 'EOF'
your prompt
EOF
Chat with File
ocw chat <hash> -f /path/to/spec.md << 'EOF'
implement based on this
EOF
Worktree Workflow
ocw new gpt --worktree→ get hash + path- Work in worktree:
cd /path/to/ocw-{hash} - Edit, commit, push as needed
- When done:
git worktree remove /path/to/ocw-{hash}
List Sessions
ocw list
Decide Fit First
Design Intent
How To Use It
Boundaries And Review