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.
npx skills add get-convex/agent-skills --skill convex-seedgit clone --depth 1 https://github.com/get-convex/agent-skillsWrote 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.
[](https://agentmods.dev/skills/get-convex/agent-skills/convex-seed)<a href="https://agentmods.dev/skills/get-convex/agent-skills/convex-seed"><img src="https://agentmods.dev/badge/skills/get-convex/agent-skills/convex-seed/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.
<a href="https://agentmods.dev/skills/get-convex/agent-skills/convex-seed"><img src="https://agentmods.dev/badge/skills/get-convex/agent-skills/convex-seed.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
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.
| Model | Per session | Once 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 |
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 10d 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.
This is a copy
100% identical to convex-seed — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Seed / import data
Populate tables via an internalMutation seed function (re-runnable) or npx convex import, matching the schema.
Workflow
- For fixtures: write an internalMutation that inserts sample rows; run it with
npx convex run. - For bulk import: shape the data to the schema and use
npx convex import. - Make seeding idempotent (clear-then-insert or upsert) so re-running is safe.
- Verify row counts.
Rules
- Seed via internalMutation or convex import, matching validators.
- Make seeding idempotent.
- Never seed secrets/PII into a shared deployment.
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.
- 10d ago First seen · 24 lines · 15 tokens per session scan A 4dddfb3f91da
convex-seed is a skill published in the GitHub repository get-convex/agent-skills (55 stars, last pushed today), licensed Apache-2.0. 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. It is 100% identical to convex-seed, differing in 0 lines, and is treated as a copy.
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