convex-deployment

convex-deployment is a skill for Claude Code, Codex from withoneai/one-agent-plugin. It costs 122 tokens per session (1,451 once invoked), scanned A, original, MIT.

A deployment service for Convex applications, where backend functions, database schemas, indexes, and settings are managed together. It supports development, preview, and production environments.

In plain words
What is it for?
It helps developers deploy Convex backend code and database changes, create preview deployments, and publish tested updates to production.
Why use it?
It provides separate places to test and review changes before applying them to the live application.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit It helps developers deploy Convex backend code and database changes, create preview deployments, and publish tested updates to production.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/withoneai/one-agent-plugin/convex-deployment
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add withoneai/one-agent-plugin --skill convex-deployment
Clone the repo
git clone --depth 1 https://github.com/withoneai/one-agent-plugin

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for convex-deployment

README.md
[![agentmods](https://agentmods.dev/badge/skills/withoneai/one-agent-plugin/convex-deployment/github.svg)](https://agentmods.dev/skills/withoneai/one-agent-plugin/convex-deployment)
Your own site
<a href="https://agentmods.dev/skills/withoneai/one-agent-plugin/convex-deployment"><img src="https://agentmods.dev/badge/skills/withoneai/one-agent-plugin/convex-deployment/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for convex-deployment

Your own site · 80×15
<a href="https://agentmods.dev/skills/withoneai/one-agent-plugin/convex-deployment"><img src="https://agentmods.dev/badge/skills/withoneai/one-agent-plugin/convex-deployment.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 122 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,451 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00122 $0.01451
Opus 5 $0.00061 $0.00726
Sonnet 5 $0.00024 $0.00290
Haiku 4.5 $0.00012 $0.00145

Measured 5d ago against content hash 570411415989, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

convex-deployment scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

platforms/one-convex-deployment/skills/convex-deployment/SKILL.md · 91 lines

How it starts

The opening of the file, as written. The whole thing — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Convex Deployment through One

Convex Deployment enables developers to deploy backend functions, database schema, indexes, and configuration for applications built on the Convex platform. It supports development, preview, and production deployments, allowing teams to safely test changes and push updates to live applications.

One exposes Convex Deployment through four MCP tools. The table below carries real action ids from One's knowledge base, so for a common operation you can skip search and go straight to reading the action's parameters.

How to run an action

  1. Find the action in the table below, or call search_one_platform_actions with platform convex-deployment if it is not listed.
  2. Call get_one_action_knowledge with the action id. Do this every time, including for actions in this table. The table gives you the id, not the parameters.
  3. Call execute_one_action with parameters copied from that knowledge.

Never guess a parameter name, a body field, or an enum value. The knowledge has the real schema, and a guessed field is either a 400 or a silent write of the wrong thing.

Before you start

Call list_one_integrations once and confirm Convex Deployment is connected. If it is missing, the user has not connected it: say so and point them at https://app.withone.ai rather than reaching for raw HTTP.

Each connection carries an access field. If it reports {"policy": "methods", "methods": ["GET"]} the agent is read-only here, so plan a read-only answer instead of attempting a write that will be refused.

Before a write

Creates, updates, deletes and sends land on a real Convex Deployment account and cannot be recalled. State the action and the specific target in one line before the first write in a task, and let the user stop you. Reads need no confirmation.

Actions

StreamingImport

Action Method Path Action id
Check If Primary Key Indexes Are Ready For Tables (Streaming Import) GET /api/streaming_import/primary_key_indexes_ready conn_mod_def::GJ2KeQs7HxE::uhmkNqnARo-AyqRXGkHyXg
Add Primary Key Indexes for Streaming Import PUT /api/streaming_import/add_primary_key_indexes conn_mod_def::GJ2KeJR5DnA::JSZXzng9TyufDlfnMH1P-g
Clear Tables via Streaming Import PUT /api/streaming_import/clear_tables conn_mod_def::GJ2KeYfUpoU::2mhFWSpqSOuSDdOkAvKG4g
Streaming Import Airbyte Records POST /api/streaming_import/import_airbyte_records conn_mod_def::GJ2Keg50DiI::Vo1qeOYRQu6f3Jt90Jf7yA

Read the full file on GitHub · 91 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 5d ago First seen · 91 lines · 0 tokens per session scan A 570411415989

Subscribe to this mod's changes

convex-deployment is a skill published in the GitHub repository withoneai/one-agent-plugin (1 stars, last pushed 19d ago), licensed MIT. It adds 122 tokens to every session and 1,451 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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