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View or modify Warp application settings using the bundled JSON schema for guidance
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Fetch and display GitHub PR review comments for the current branch.
**MANDATORY prerequisite** — you MUST invoke this skill BEFORE every `use_figma` tool call. NEVER call `use_figma` directly without loading this skill first. Skipping it causes common, hard-to-debug failures. Trigger whenever the user wants to perform a write action or a unique read action that requires JavaScript execution in the Figma file context — e.g. create/edit/delete nodes, set up variables or tokens, build components and variants, modify auto-layout or fills, bind variables to properties, or inspect file structure programmatically.
Guides testing Warp UI features and changes using the computer use tool. Use this skill only when the computer_use tool is available to the agent. Covers launching Warp and verifying UI behavior.
Repo-specific review guidance for warp. Only the categories declared overridable by the core review-pr skill may be specialized here.
Control and inspect the currently running local Warp application with the warpctrl CLI. Use this skill whenever the user asks the agent to manipulate Warp's own windows, tabs, panes, sessions, input buffer, themes, or UI surfaces; open a file in Warp; inspect local Warp state; or explain how to invoke Warp Control manually.
Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
| name | modify-settings |
| description | View or modify Warp application settings using the bundled JSON schema for guidance |
Use this skill when the user wants to view, change, or troubleshoot Warp application settings.
A JSON schema describing all available settings is bundled at:
{{settings_schema_path}}
The schema follows JSON Schema draft 2020-12, with settings organized hierarchically under properties. Each setting includes:
description — what the setting controlstype — the value type (string, boolean, integer, etc.)default — the default valueenum or oneOf — valid values, when the setting is constrainedUse grep to do an initial broad search for candidate key names:
grep -i "font" {{settings_schema_path}}
Once you have a candidate key name, run the bundled script to get the full dotted path, the setting's properties, and any parent context. This is critical — the schema has multiple sections with similar names (e.g. several input keys), so never assume the nesting from grep output alone.
python3 {{skill_dir}}/scripts/find_setting.py {{settings_schema_path}} <key_name>
The output gives you the unambiguous full path (e.g. properties.appearance.properties.input.properties.input_mode) and the setting's full definition including valid values.
The user's settings are stored in a TOML file at:
{{settings_file_path}}
Settings use dotted TOML section headers matching the schema hierarchy. Always trace the full nesting path from the schema to the TOML — each intermediate properties key becomes a section level. For example:
A property at properties.appearance.properties.font_size (one level deep) corresponds to:
[appearance]
font_size = 14
A property at properties.appearance.properties.themes.properties.theme (two levels deep) corresponds to:
[appearance.themes]
theme = "light"
A common mistake is to stop one level too early — always count the full depth before writing the TOML section header.
If the file does not exist yet, create it. Warp hot-reloads this file, so changes take effect immediately.
grep to identify candidate key names, then run the Python path-tracing script to get the full dotted path and the setting's valid values. Never rely on grep output alone to infer nesting.