convex-seed

convex-seed is a skill for Claude Code, Codex from openclaw/clawhub. It costs 15 tokens per session (183 once invoked), scanned A, original, MIT.

A guide for adding fixture or imported data to a Convex database. Fixtures are sample records used for development or testing.

In plain words
What is it for?
Use it to create re-runnable seed functions, perform bulk imports, match data to the Convex schema, and verify imported row counts.
Why use it?
It makes data setup repeatable and reduces the risk of duplicate records or accidentally shared secrets and personal data.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: installed under .agents/ (shared by several agents).

Good fit Use it to create re-runnable seed functions, perform bulk imports, match data to the Convex schema, and verify imported row counts.

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Install with agentmods
npx agentmods add skills/openclaw/clawhub/convex-seed
About the project

ClawHub is a public registry where OpenClaw users publish, version, search, and install text-based agent skills and OpenClaw packages. It provides web browsing, a CLI-oriented API, moderation, vector search, and artifact hosting for code plugins, bundle plugins, and experimental whole-agent packages. The catalogue skills and agents are entries that can be discovered or used through this registry.

openclaw/clawhub · 9,399 stars · on GitHub · clawhub.ai

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 openclaw/clawhub --skill convex-seed
Clone the repo
git clone --depth 1 https://github.com/openclaw/clawhub

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-seed

README.md
[![agentmods](https://agentmods.dev/badge/skills/openclaw/clawhub/convex-seed.svg)](https://agentmods.dev/skills/openclaw/clawhub/convex-seed)
Your own site
<a href="https://agentmods.dev/skills/openclaw/clawhub/convex-seed"><img src="https://agentmods.dev/badge/skills/openclaw/clawhub/convex-seed.svg" alt="Measured on agentmods" height="20"></a>
Per session 15 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 183 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. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 3 findings, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium MCP Rug Pull · line 10
    npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.
    Fix: Pin the version: npx @scope/[email protected]
  • medium MCP Rug Pull · line 14
    npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.
    Fix: Pin the version: npx @scope/[email protected]
  • medium MCP Rug Pull · line 15
    npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.
    Fix: Pin the version: npx @scope/[email protected]
How audits are shown
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 $0.00015 $0.00183
Opus 5 $0.00008 $0.00092
Sonnet 5 $0.00003 $0.00037
Haiku 4.5 $0.00002 $0.00018

Measured 8d ago against content hash 4dddfb3f91da, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

convex-seed 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 8d 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

.agents/skills/convex-seed/SKILL.md · 24 lines

What it actually says

Seed / import data

Populate tables via an internalMutation seed function (re-runnable) or npx convex import, matching the schema.

Workflow

  1. For fixtures: write an internalMutation that inserts sample rows; run it with npx convex run.
  2. For bulk import: shape the data to the schema and use npx convex import.
  3. Make seeding idempotent (clear-then-insert or upsert) so re-running is safe.
  4. Verify row counts.

Rules

  • Seed via internalMutation or convex import, matching validators.
  • Make seeding idempotent.
  • Never seed secrets/PII into a shared deployment.
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. 8d ago First seen · 24 lines · 15 tokens per session scan A 4dddfb3f91da

Subscribe to this mod's changes

convex-seed is a skill published in the GitHub repository openclaw/clawhub (9,399 stars, last pushed yesterday), licensed MIT. It adds 15 tokens to every session and 183 once invoked, about $0.0001 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 2026-08-30.