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convexconvex/agent-skills/skills/convex-sentinel/SKILL.md

convex-sentinel

Skill68 starsChanged 15 days agoApache-2.0View on GitHub

Set up Sentinel production error capture in your own Convex deployment.

6 other projects use a version of this.

Adopted by

Steady: 0 new projects took it in the last 4 weeks, none the 4 weeks before.thin data

Week of Sep 13: 0 new projectsWeek of Sep 20: 0 new projectsWeek of Sep 27: 0 new projectsWeek of Oct 4: 0 new projectsWeek of Oct 11: 0 new projectsWeek of Oct 18: 0 new projectsWeek of Oct 25: 0 new projectsWeek of Nov 1: 0 new projects
Sep 2026Oct 2026Nov 2026
New projects taking a version of this file each week, over the 8 weeks our latest run read: only 0 in all, so this is a hint, not a trend.

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Used with

Projects with it also use convex-acquire-domain, convex-check-updates and 10 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • FabienGreardSkill

    convex-acquire-domain

    Find and buy a domain for the current Convex app through Convex, then bind it (labs; spend action).

    Also in 4 projects that use this

  • FabienGreardSkill

    convex-check-updates

    Check the current app's pinned Convex components against recommended versions and upgrade them behind a build gate.

    Also in 4 projects that use this

  • openclawSkill

    clawhub-ban-appeals

    Review ClawHub account-ban appeals, distinguish bans from moderation holds or blocked releases, and prepare an evidence-backed moderation decision. Route validated scanner inaccuracies to clawhub-clawscan.

    Also in 3 projects that use this

  • openclawSkill

    clawhub-clawscan

    Investigate ClawScan health alerts, diagnose scanner or ClawHub integration failures, prepare operational repairs, and route validated verdict inaccuracies upstream. Account ban appeals use clawhub-ban-appeals.

    Also in 3 projects that use this

  • +8 more from openclaw

The file

We split this skill into the rules it gives an agent

1 rule. About 0 are common, 0 are distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈0

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Read recent errors with the Convex CLI (convex data, run-once-query).

    line 17

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md
<!-- GENERATED from convex-agents content/capabilities/sentinel.json — do not edit by hand. -->

Capture production errors in your own deployment

Install @convex-dev/sentinel to capture production errors (server function failures, client JS/React crashes, OCC and scale signals) into a table in the user's OWN deployment, redacted at write time, then react to new ones. Data never leaves the user's deployment.

Workflow

  1. Install the component: app.use(sentinel) in convex/convex.config.ts.
  2. Wire the client SDK: a React error boundary plus window.onerror/unhandledrejection and breadcrumbs.
  3. Redaction runs at write time and is on by default (default-deny on secret key names and value patterns).
  4. Read recent errors with the Convex CLI (convex data, run-once-query); react to new ones via the monitor's prod_error event.
  5. Optionally enable the self-healing cron: triage classifies each error and, for recurring non-transient ones, hands it to ai-runner to open a fix PR.

Rules

  • Redaction is mandatory and on by default — never store raw secrets; the agent's reads reach the model provider.
  • Data stays in the user's deployment; never send it to a third party.
  • Sample and cap to control volume and cost.
  • Capturing PROD errors needs a deployed cloud app; install works anonymously.

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