Official agent skill

Expo Skill Feedback

by expo in expo/skills

Submit feedback on an Expo skill—or Expo itself—and control bundled anonymous usage telemetry (off by default / opt-in).

OfficialMITAuto-check passedMobile

Install Expo Skill Feedback

skills CLI
$ npx skills add expo/skills --skill expo-skill-feedback -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install expo/skills expo-skill-feedback --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/expo/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/expo/skills/expo-skill-feedback .claude/skills/expo-skill-feedback && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
expo-skill-feedback
GitHub stars
2.7k
Token cost
~1.3k tokens
SKILL.md length
556 words
Files
5 (incl. scripts)
Skills in repo
26
Repo updated
First seen
Licence
MIT

At a glance

Submit feedback on an Expo skill—or Expo itself—and control bundled anonymous usage telemetry (off by default / opt-in).

  • A skill was useful
  • SKILL.md covers Submit feedback, Eval candidates: tasks that…, Usage telemetry and Submitting Feedback
  • Runs JavaScript scripts from its folder; calls npx, eas and node
  • Missing context

What it does

Expo Skill Feedback is an agent skill from expo/skills, published by the product's own GitHub organization. Submit feedback on an Expo skill—or Expo itself—and control bundled anonymous usage telemetry (off by default / opt-in). Submit feedback with: npx --yes submit-expo-feedback@latest "ACTIONABLEFEEDBACK". Optionally add either or both: --category "CATEGORY" and --subject "SUBJECT". Replace the uppercase placeholders before running. Use when a skill was useful, confusing, broken, missing context, or worth improving; when Expo, Expo CLI, EAS CLI, docs, or MCP worked well or fell short; when an AI agent repeatedly…

Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including scripts (for example `agents/openai.yaml`).

It sits in Mobile, covering Cross-platform mobile apps. It works with Expo and Model Context Protocol. The repository describes itself as: A collection of AI agent skills for working with Expo projects and Expo Application Services. The licence is MIT.

When your agent uses it

  • A skill was useful
  • Missing context
  • Worth improving
  • MCP worked well

Example prompts

  • “ACTIONABLEFEEDBACK”
  • “CATEGORY”
  • “SUBJECT”
  • “/expo-skill-feedback”

Requirements

  • Node.js

What it can do on your machine

Read from SKILL.md and the folder at commit d4f4840. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 3 files in scripts/ (JavaScript), which the agent can run.

    Shell commands in SKILL.md call:

    • npx
    • eas
    • node

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use npx, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Expo Skill Feedback loads about 1.3k tokens when it runs. Until then it costs about 190 tokens; SKILL.md has 556 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~190
When it runs · the whole SKILL.md, loaded when a task matches
~1.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from expo/skills at commit d4f4840, republished under its MIT licence (© expo). 556 words, ~1,295 tokens.

Download SKILL.mdSave it as .claude/skills/expo-skill-feedback/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
expo-skill-feedback
description
Submit feedback on an Expo skill—or Expo itself—and control bundled anonymous usage telemetry (off by default / opt-in). Submit feedback with: npx --yes submit-expo-feedback@latest "ACTIONABLE_FEEDBACK". Optionally add either or both: --category "CATEGORY" and --subject "SUBJECT". Replace the uppercase placeholders before running. Use when a skill was useful, confusing, broken, missing context, or worth improving; when Expo, Expo CLI, EAS CLI, docs, or MCP worked well or fell short; when an AI agent repeatedly failed, got stuck, or needed the user to take over an Expo task (report it as an eval candidate); or when the user explicitly asks to enable or disable telemetry (tracking), check its status, or understand what it collects.

Expo Skill Feedback

Help Expo improve by sharing specific feedback about what worked well or what fell short. Feedback submission is independent of usage telemetry and does not require enabling it.

Submit feedback

bash
npx --yes submit-expo-feedback@latest "<ACTIONABLE_FEEDBACK>"

Add either optional flag independently when it provides useful context:

bash
npx --yes submit-expo-feedback@latest --category "<CATEGORY>" --subject "<SUBJECT>" "<ACTIONABLE_FEEDBACK>"

--category defaults to unknown, and --subject may be omitted when there is no specific target. When including them, choose the values that most precisely identify what the feedback is about:

CategorySubject
skillsExact skill name from its frontmatter, such as expo-router
docsFull Expo documentation URL
mcpExact MCP tool name used
expo-cliFull Expo CLI command, such as npx expo install
eas-cliFull EAS CLI command, such as eas build
evalsExpo package or command the failed task involves, else a capability phrase, such as expo-router or eas build
unknownConcise Expo product, package, feature, or other topic

In the final argument, say what helped and why, or provide the relevant context, expected behavior, and what happened instead. Do not include secrets, source code, personal data, long prompts, or stack traces.

Eval candidates: tasks that broke the model

Expo turns hard real-world tasks into agent evals: anything Expo an agent can attempt — framework, EAS, tooling — qualifies, whether or not a skill was involved. The signal worth sending is a task an AI agent could not complete cleanly despite real effort: several failed attempts, a build or screen that never worked, or the user stepping in to fix it manually. Never submit quick slips the agent corrected itself, more than one candidate per session, or a task already reported.

When such a failure happens — or the user says a model failed at an Expo task — show the user the exact submission you intend to send and get approval; the Task field must describe the Expo-technical shape of the task, never the user's product or business context. Without a user to approve it (headless or CI runs), do not submit. Then run from the failing app's directory (the CLI attaches the SDK and package versions, agent harness, and platform automatically) with --category evals, --subject naming the Expo package or command involved (a capability phrase only when no single package fits), and this structure in the final argument:

Show full SKILL.md (186 more words)Show less
text
Task: <what was asked, self-contained>.
Expected: <observable success criteria>.
Actual: <what the agent did instead>.
Wrong approach: <the specific mistake, such as a wrong API, hallucinated prop, or bad pattern>.
Evidence: <model name, attempts, how it was solved — or never was; omit what you cannot verify>.

A good candidate is solvable (eventually done or clearly doable), verifiable (success is observable), and specific. Mention only environment details the CLI cannot see, such as other key packages or a freshly created app. Describe code; do not paste it. If the command fails with an error naming evals as an invalid category, resend once with --category unknown and the same subject prefixed eval-candidate: ; on any other error, do not resend.

Usage telemetry

Automatic skill usage telemetry is separate from feedback and off by default. Never enable it without an explicit user request. Use the following script with --on, --off, or --status:

bash
node "${CLAUDE_PLUGIN_ROOT}/skills/expo-skill-feedback/scripts/telemetry.cjs" --status

Environment equivalents are EXPO_SKILLS_TELEMETRY=1 to enable and EXPO_SKILLS_TELEMETRY=0 or DO_NOT_TRACK=1 to disable. CI never sends telemetry.

Submitting Feedback

If you encounter errors, misleading or outdated information in this skill, report it so Expo can improve:

bash
npx --yes submit-expo-feedback@latest --category skills --subject "expo-skill-feedback" "<actionable feedback>"

Only submit when you have something specific and actionable to report. Include as much relevant context as possible. If an AI agent repeatedly failed or the user had to take over an Expo task, load the expo-skill-feedback skill and follow its eval-candidate flow instead of reusing the command above.

© expo, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files (scripts) in plugins/expo/skills/expo-skill-feedback of expo/skills.

  • SKILL.md
  • agents/openai.yaml
  • scripts/skill-event.cjs
  • scripts/telemetry.cjs
  • scripts/telemetry_common.cjs

Open the folder on GitHubat commit d4f4840

Compare with similar skills

Expo Skill Feedback next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Expo Skill Feedback compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Expo Skill Feedback this skillexpo/skills2.7k—~1.3kAutomated safety check: PassMIT
Appllama App Design SkillAppllama/appllama-skills2.5k1 repos~5kAutomated safety check: PassMIT
Appllama UsageAppllama/appllama-skills2.5k1 repos~1.6kAutomated safety check: PassMIT
Release Sample SweepAtmosphere/atmosphere3.8k—~4.2kAutomated safety check: PassApache-2.0
QA Find Bugs Mobilebex-co/beancount-io296—~2.2kAutomated safety check: NotesMIT
Radon MCPsoftware-mansion-labs/skills291—~665Automated safety check: PassNone

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Categories

Questions about Expo Skill Feedback

What does Expo Skill Feedback do?

Submit feedback on an Expo skill—or Expo itself—and control bundled anonymous usage telemetry (off by default / opt-in). Expo Skill Feedback is an agent skill from expo/skills, published by the product's own GitHub organization. Submit feedback on an Expo skill—or Expo itself—and control bundled anonymous usage telemetry (off by default / opt-in).

When should I use Expo Skill Feedback?

Expo Skill Feedback fits situations like: A skill was useful; missing context; worth improving; MCP worked well.

How do I install Expo Skill Feedback in Claude Code?

Run `npx skills add expo/skills --skill expo-skill-feedback -a claude-code`. Or copy the skill folder (plugins/expo/skills/expo-skill-feedback in expo/skills) into .claude/skills/expo-skill-feedback in your project. Claude Code loads it when a task matches its description.

How do I install Expo Skill Feedback in Codex?

Run `npx skills add expo/skills --skill expo-skill-feedback -a codex`. Or copy the skill folder (plugins/expo/skills/expo-skill-feedback in expo/skills) into .agents/skills/expo-skill-feedback in your project. Codex loads it when a task matches its description.

Can I use Expo Skill Feedback in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add expo/skills --skill expo-skill-feedback -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/expo-skill-feedback, .gemini/skills/expo-skill-feedback, .github/skills/expo-skill-feedback and .opencode/skills/expo-skill-feedback in your project.

What does Expo Skill Feedback need to run?

Going by SKILL.md and its folder, Expo Skill Feedback needs JavaScript for the scripts in its folder and the command-line tools its instructions call (npx, eas and node). Our summary lists: Node.js.

Does Expo Skill Feedback access the network?

SKILL.md contains no URLs. Its commands use npx, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Expo Skill Feedback safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Expo Skill Feedback use?

Expo Skill Feedback is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Expo Skill Feedback use?

About 1.3k tokens (SKILL.md is roughly 5.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Expo Skill Feedback?

Skills that share tags, products or a category with Expo Skill Feedback: Appllama App Design Skill (Appllama/appllama-skills, 2.5k stars), Appllama Usage (Appllama/appllama-skills, 2.5k stars), Release Sample Sweep (Atmosphere/atmosphere, 3.8k stars) and QA Find Bugs Mobile (bex-co/beancount-io, 296 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Expo Skill Feedback?

expo (a GitHub organization, an official publisher) maintains it in expo/skills, which has 2,685 GitHub stars. The repository holds 26 skills in this directory. The repository was last updated on October 7, 2026.

Source: expo/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.