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Skills/get-convex/agent-skills/convex-deploy-guard
convex-deploy-guard logo

convex-deploy-guard

get-convex/agent-skills
963 installs42 stars
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Installation

npx skills add https://github.com/get-convex/agent-skills --skill convex-deploy-guard

Summary

Classify + announce the target Convex deployment before any deployment-affecting command; fresh explicit consent for prod actions; session read-only mode.

SKILL.md

<!-- GENERATED from convex-agents content/capabilities/deploy-guard.json — do not edit by hand. -->

Deployment target guard

Deployments are not interchangeable, and most incidents start with a command aimed at the wrong one. Every Convex project has several (personal dev, preview, prod — often across multiple projects on one machine). This guard is the standing discipline: identify, announce, then act — and treat prod as consent-gated, per action, per session.

Workflow

  1. IDENTIFY before you act: read CONVEX_DEPLOYMENT in .env.local, convex.json, and whether CONVEX_DEPLOY_KEY is set; or call the official Convex MCP status tool. Classify the target: local-anonymous | dev | preview | prod. If two sources disagree, resolve before proceeding.
  2. ANNOUNCE in one line before any deployment-affecting command: target: dev (joyful-capybara-123, personal dev). Never run the command in the same breath as discovering the target — announce first.
  3. PROD needs a FRESH explicit yes: before npx convex deploy (when it resolves to prod), npx convex run --prod, env set on prod, snapshot import/export on prod, or starting the MCP with prod access — state exactly what will change on which deployment and get an explicit yes in THIS session. A yes given earlier, or for a different target, does not carry.
  4. MCP safety defaults: start the official MCP scoped non-prod (--deployment dev). The two prod flags are DIFFERENT risk levels — keep them split: a read-only prod audit (advisor/insights reading data/logs/insights) passes ONLY --cautiously-allow-production-pii (read tools); --dangerously-enable-production-deployments (which enables MUTATING prod tools) stays OFF unless the user explicitly asked to CHANGE prod this session. Never pair them by default — 'look at prod' must not silently grant 'mutate prod'.
  5. READ-ONLY session mode: when the user says 'read-only' / 'don't change anything', honor it absolutely for the rest of the session — no deploy, no env set/remove, no mutations via run, no imports; start the MCP with --disable-tools run,envSet,envRemove.
  6. Wrong-deployment diagnosis: when a deploy 'didn't change anything', do NOT re-deploy harder. Re-run step 1 — the deploy almost certainly landed on a different deployment than the one being observed.
  7. Ambiguity = stop: if you cannot determine which deployment a command will hit, find out (status tool; compare npx convex env list fingerprints) — never guess.

Rules

  • Classify and announce the target BEFORE every deployment-affecting command — identification and action are two separate steps.
  • Prod consent is per-action, per-target, per-session: state what changes where, get a fresh explicit yes.
  • Keep the two prod MCP flags split by risk: --cautiously-allow-production-pii (read-only) for an audit; --dangerously-enable-production-deployments (mutating) only when the user explicitly asks to change prod. Both are user-spoken-only; default every MCP start to a non-prod deployment selector.
  • Read-only mode, once requested, is absolute for the session — including 'harmless' mutations.
  • A deploy that seemed to do nothing means the WRONG deployment changed — diagnose the target, don't re-run.
  • This guard composes: ship, env, migrate, and seed run it as their step 0; it is not itself a deploy tool.

Score

0–100
63/ 100

Grade

C

Popularity15/30

963 installs — growing adoption.

Completeness27/30

Documented: full SKILL.md body, description, one-line install. Missing: category/license metadata.

Trust15/25

Community skill with a public GitHub source repository you can review.

Freshness6/15

No update timestamp is tracked for this skill in our catalog.

Scored automatically from popularity, completeness, trust, and freshness — computed only from data in our catalog, never fabricated.

Proud of your score? Add this badge to your README.

Paste a snippet into your GitHub README. The badge updates automatically and links back to this page.

Convex Deploy Guard skill score badge previewScore badge

Markdown

[![Convex Deploy Guard skill](https://www.claudemarket.ai/skills/get-convex/agent-skills/convex-deploy-guard/badges/score.svg)](https://www.claudemarket.ai/skills/get-convex/agent-skills/convex-deploy-guard)

HTML

<a href="https://www.claudemarket.ai/skills/get-convex/agent-skills/convex-deploy-guard"><img src="https://www.claudemarket.ai/skills/get-convex/agent-skills/convex-deploy-guard/badges/score.svg" alt="Convex Deploy Guard skill"/></a>

Convex Deploy Guard FAQ

How do I install the Convex Deploy Guard skill?

Run “npx skills add https://github.com/get-convex/agent-skills --skill convex-deploy-guard” in your terminal. The skill is added to your agent's skills directory and picked up automatically on the next run — no restart or extra configuration needed.

What does the Convex Deploy Guard skill do?

Classify + announce the target Convex deployment before any deployment-affecting command; fresh explicit consent for prod actions; session read-only mode. The full SKILL.md on this page shows the exact instructions the skill gives your agent.

Is the Convex Deploy Guard skill free?

Yes. Convex Deploy Guard is a free, open-source skill published from get-convex/agent-skills. As with any third-party skill, review the source repository before installing it into an agent with sensitive access.

Does Convex Deploy Guard work with Claude Code and OpenClaw?

Yes. Skills use the portable SKILL.md format, so Convex Deploy Guard works with Claude Code, OpenClaw, Codex, Hermes, and any other agent that reads SKILL.md skills.

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