What does this skill do, and when should you use it?
Expo Skill Feedback is an open-source skill in the official Expo skills collection. It lets users rate an Expo skill or report an issue caused by Expo itself. Anonymous telemetry is opt-in and remains off until the user explicitly enables it. It fits Expo developers who want to help improve the skill collection while retaining control over telemetry.
It runs the bundled Node.js scripts to submit feedback with --skill, --rating, --text, and optionally --about. The --dry-run option prints the payload without sending it. The telemetry.cjs script supports --on, --off, and --status for changing or checking telemetry state. When enabled, feedback is sent through PostHog and contains the skill name, rating, note, platform, and a hash of a random local install ID.
- An Expo developer found a skill useful and wants to submit a useful rating.
- A user encountered confusing, outdated, missing, or broken skill guidance and wants to report it.
- A user believes the problem is caused by Expo SDK or framework behavior rather than the skill and wants to report it as an Expo issue.
- A user wants to check, enable, or disable anonymous Expo skills telemetry.
How do you install this skill?
- The skill-feedback.cjs and telemetry.cjs source and tests were not supplied, so actual data flow, error handling, and status coverage cannot be verified.
- Telemetry and feedback depend on external PostHog; mainland-China reachability, retention policy, and transport security are not established by the materials.
- Telemetry must not be enabled without explicit consent, and feedback text still requires manual exclusion of secrets, source code, prompts, and stack traces.
- Shell / CLI
- Network access
- Local filesystem
Node.js
The skill is installed as part of the expo/skills collection. For Codex, run: codex plugin add expo@openai-curated. With the Skills CLI, run: npx skills@latest add expo/skills --skill '*' and choose the installation location when prompted; refresh or restart the agent session afterward. The source does not document a separate single-skill installation command.
tmp="$(mktemp -d)"
git clone --depth 1 https://github.com/expo/skills.git "$tmp"
mkdir -p ~/.claude/skills
cp -R "$tmp/plugins/expo/skills/expo-skill-feedback" ~/.claude/skills/
rm -rf "$tmp"Generated from the source repository and skill path; it copies only this skill's folder. If the author's install steps above differ, follow those first. To scope it to one project, replace ~/.claude/skills with that project's .claude/skills.
How do you use this skill?
Once installed, send your agent any of these to trigger it:
- enable Expo skills telemetry
- TestFlight steps were clear and worked first try.
In conversation, saying “enable Expo skills telemetry” requests telemetry activation; run telemetry.cjs --on only after explicit user consent. To submit feedback, run skill-feedback.cjs with the rated skill name, rating, and note, for example: node "${CLAUDE_PLUGIN_ROOT}/skills/expo-skill-feedback/scripts/skill-feedback.cjs" --skill eas-app-stores --rating useful --text "TestFlight steps were clear and worked first try." Use telemetry.cjs --status to check state and --off to disable it.
What are this skill's strengths and limitations?
- Telemetry is off by default and can be explicitly enabled, disabled, or checked.
- Feedback categories and command parameters are clearly defined.
- The source states that code, prompts, file paths, secrets, and personal data are not sent.
- Requires Node.js and an agent environment able to run shell scripts.
- Sending feedback requires network access and uses PostHog.
- Its scope is limited to Expo skill feedback, Expo framework feedback, and telemetry controls; it does not provide general Expo development features.
- The source provides no test suite or independent platform-validation evidence.
How does this skill compare with similar options?
Side by side with related skills; every score comes from the same FSRS standard.
| Skill | FS score | Stars | Last updated | License |
|---|---|---|---|---|
| Expo Skill Feedback this page | 54 · Use with care | ★ 2.9k | 21d ago | MIT |
| React Native Performance Guide | 60 · Recommended | ★ 1.7k | 18d ago | MIT |
| Expo Native UI Builder | 59 · Recommended | ★ 2.9k | 21d ago | MIT |
| Expo Brownfield Integrator | 58 · Recommended | ★ 2.9k | 21d ago | MIT |
| Expo App Structure Guide | 57 · Use with care | ★ 2.9k | 21d ago | MIT |
The README identifies Expo documentation, Expo CLI, and EAS CLI as the sources of truth. This skill manages feedback and telemetry; it does not replace those tools or documentation.
How did FollowSkills review this skill?
The documentation clearly states that telemetry is off by default, requires explicit user consent, discloses the transmitted fields, prohibits sensitive content, and provides opt-out controls. However, sending depends on external PostHog, while implementation, transport security, retention, and auditable rollback details are absent, so 5 points are deducted.
The commands, switch semantics, and handling after a refusal are broadly self-consistent, and CI behavior is described. This was only a static review: scripts, tests, locked dependencies, key-path execution evidence, and robust abnormal-input diagnostics are missing, so 2 points are deducted.
Use cases, rating values, telemetry controls, and boundaries around sensitive content are reasonably clear. Chinese-language support is not documented, and the core feedback/telemetry path depends on PostHog, whose reachability from mainland China cannot be established from the supplied material, so 6 points are deducted.
The skill has clear structure, parameters, examples, privacy limits, and README installation guidance. The repository provides an MIT license and CI maintenance signals, but the selected skill lacks versioning, changelog, named maintenance responsibility, and a clear update path, so 7 points are deducted.
The skill directly targets submitting concise feedback and managing telemetry, with usable commands and expected inputs. Static material does not establish that the scripts run, deliver feedback successfully, or relay status correctly; the static cap therefore limits the score to 6.
The README and skill document corroborate the main behavior, and repository CI provides some maintenance evidence. The key scripts and tests are not supplied, while privacy and PostHog behavior remain author claims without third-party or reproducible evidence, so 2 points are deducted.
Open a dimension to read why it scored that way
Evidence confidence：Low — Mostly static review, author material or a limited demo; useful for discovery, not high-risk decisions.
See the full review method →