string-reviewer
Use this skill when asked to review text and user-facing strings within the codebase. It ensures that these strings follow rules on clarity, usefulness, brevity and style.
- Installs
- 390
- Last 24h
- —
- Trending rank
- —
- Security
- Not audited
Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/google-gemini/gemini-cli --skill string-reviewer- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads string-reviewer automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
String Reviewer
Instructions
Act as a Senior UX Writer. Look for user-facing strings that are too long, unclear, or inconsistent. This includes inline text, error messages, and other user-facing text.
Do NOT automatically change strings without user approval. You must only suggest changes and do not attempt to rewrite them directly unless the user explicitly asks you to do so.
Core voice principles
The system prioritizes deterministic clarity over conversational fluff. We provide telemetry, not etiquette, ensuring the user retains absolute agency..
- Deterministic clarity: Distinguish between certain system/service states (Cloud Billing, IAM, the System) and probabilistic AI analysis (Gemini).
- System transparency: Replace "Loading..." with active technical telemetry (e.g., Tracing stack traces...). Keep status updates under 5 words.
- Front-loaded actionability: Always use the [Goal] + [Action] pattern. Lead with intent so users can scan left-to-right.
- Agentic error recovery: Every error must be a pivot point. Pair failures with one-click recovery commands or suggested prompts.
- Contextual humility: Reserve disclaimers and "be careful" warnings for P0 (destructive/irreversible) tasks only. Stop warning-fatigue.
The writing checklist
Use this checklist to audit UI strings and AI responses.
Identity and voice
- Eliminate the "I": Remove all first-person pronouns (I, me, my, mine).
- Subject attribution: Refer to the AI as Gemini and the infrastructure as the - system or the CLI.
- Active voice: Ensure the subject (Gemini or the system) is clearly performing the action.
- Ownership rule: Use the system for execution (doing) and Gemini for analysis (thinking)
Structural scannability
- The skip test: Do the first 3 words describe the user’s intent? If not, rewrite.
- Goal-first sequence: Use the template: [To Accomplish X] + [Do Y].
- The 5-word rule: Keep status updates and loading states under 5 words.
- Telemetry over etiquette: Remove polite filler (Please wait, Thank you, Certainly). Replace with raw data or progress indicators.
- Micro-state cycles: For tasks $> 3$ seconds, cycle through specific sub-states (e.g., Parsing logs... ➔ Identifying patterns...) to show momentum.
Technical accuracy and humility
- Verb signal check: Use deterministic verbs (is, will, must) for system
state/infrastructure.
- Use probabilistic verbs (suggests, appears, may, identifies) for AI output.
- No 100% certainty: Never attribute absolute certainty to model-generated content.
- Precision over fuzziness: Use technical metrics (latency, tokens, compute) instead of "speed" or "cost."
- Instructional warnings: Every warning must include a specific corrective action (e.g., "Perform a dry-run first" or "Review line 42").
Agentic error recovery
- The one-step rule: Pair every error message with exactly one immediate path to a fix (command, link, or prompt).
- Human-first: Provide a human-readable explanation before machine error codes (e.g., 404, 500).
- Suggested prompts: Offer specific text for the user to copy/click like “Ask Gemini: 'Explain this port error.'”
Use consistent terminology
Ensure all terminology aligns with the project word list.
If a string uses a term marked "do not use" or "use with caution," provide a correction based on the preferred terms.
Ensure consistent style for settings
If packages/cli/src/config/settingsSchema.ts is modified, confirm labels and
descriptions specifically follow the unique Settings
guidelines.
Output format
When suggesting changes, always present your review using the following list format. Do not provide suggestions outside of this list..
1. **{Rationale/Principle Violated}**
- ❌ "{incorrect phrase}"
- ✅ `"{corrected phrase}"`
FAQ
What does the string-reviewer skill do?
Use this skill when asked to review text and user-facing strings within the codebase. It ensures that these strings follow rules on clarity, usefulness, brevity and style.
How do I install string-reviewer?
Run npx skills add https://github.com/google-gemini/gemini-cli --skill string-reviewer in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/string-reviewer/ (personal) or .claude/skills/string-reviewer/ (project).
Which AI agents can use string-reviewer?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is string-reviewer safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains string-reviewer?
It is published by google-gemini in google-gemini/gemini-cli, and it is an official skill from the maker of the technology it covers. It has 390 recorded installs.
More from google-gemini/gemini-cli
code-reviewer
google-gemini/gemini-cli
Use this skill to review code. It supports both local changes (staged or working tree) and remote Pull Requests (by ID or URL). It focuses on correctness, maintainability, and adherence to project standards.
docs-writer
google-gemini/gemini-cli
Always use this skill when the task involves writing, reviewing, or editing files in the /docs directory or any .md files in the repository.
pr-creator
google-gemini/gemini-cli
Use this skill when asked to create a pull request (PR). It ensures all PRs follow the repository's established templates and standards.
docs-changelog
google-gemini/gemini-cli
Generates and formats changelog files for a new release based on provided version and raw changelog data.
pr-address-comments
google-gemini/gemini-cli
Use this skill if the user asks you to help them address GitHub PR comments for their current branch of the Gemini CLI. Requires gh CLI tool.
Popular ai & agents skills
google-agents-cli-publish
google/agents-cli
This skill should be used when the user wants to "publish an agent", "publish my ADK agent", "register an agent with Gemini", "publish to Gemini" (formerly Gemini Enterprise), or needs guidance on the agents-cli publish gemini command. Also use when the user wants to "manage agents in Agent Registry", "list/update/delete registered agents", or "register an MCP server". Covers ADK vs A2A registration modes, programmatic and interactive usage, flag reference, auto-detection from deployment metadata, Agent Registry fleet management, and troubleshooting. Part of the agents-cli skills suite. Do NOT use for deployment (use google-agents-cli-deploy).
google-agents-cli-eval
google/agents-cli
This skill should be used when the user wants to "run an evaluation", "evaluate my agent", "evaluate my ADK agent", "write an eval dataset", "analyze eval failures", "compare eval results", "optimize agent", or needs guidance on the Gemini platform eval methodology and the Quality Flywheel. Covers eval metrics, dataset schema, LLM-as-judge scoring, and common failure causes. Applies to any agents-cli project, whatever framework the agent is written in. Do NOT use for agent API code patterns (ADK: use google-agents-cli-adk-code), deployment (use google-agents-cli-deploy), or project scaffolding (use google-agents-cli-scaffold).
skill-creator
anthropics/skills
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.
codex-pet
prime-skills/runcomfy-agent-skills
Codex Pet generator on RunComfy. Build a Codex-compatible Codex Pet spritesheet.webp + pet.json from a single reference image, drop it into ${CODEXHOME:-$HOME/.codex}/pets/ / and Codex picks it up as a custom Codex Pet next to the 8 built-ins. This skill produces the exact Codex Pet atlas Codex expects (1536x1872 PNG/WebP, 8 cols x 9 rows, 192x208 cells, 9 animation states — idle, running-right, running-left, waving, jumping, failed, waiting, running, review). Calls OpenAI GPT Image 2 edit ONCE via the local RunComfy CLI as runcomfy run openai/gpt-image-2/edit to produce a canonical Codex Pet pose, then assembles all 9 animation rows programmatically with ImageMagick micro-transforms — no Codex Pro, no $imagegen, no OPENAIAPIKEY required, only RUNCOMFYTOKEN. Triggers on "codex pet", "create codex pet", "make codex pet", "hatch codex pet", "/hatch image", "desktop pet codex", "codex pets", "spritesheet.webp", or any explicit ask to build a custom pet for OpenAI Codex.
full-output-enforcement
leonxlnx/taste-skill
Overrides default LLM truncation behavior. Enforces complete code generation, bans placeholder patterns, and handles token-limit splits cleanly. Apply to any task requiring exhaustive, unabridged output.
executing-plans
obra/superpowers
Use when executing an implementation plan in the current session as the implementer yourself — your human partner chose inline execution, or no subagent tool is available