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 notque/vexjoy-agent --skill plant-seedgit clone --depth 1 https://github.com/notque/vexjoy-agentWrote 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/notque/vexjoy-agent/plant-seed)<a href="https://agentmods.dev/skills/notque/vexjoy-agent/plant-seed"><img src="https://agentmods.dev/badge/skills/notque/vexjoy-agent/plant-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/notque/vexjoy-agent/plant-seed"><img src="https://agentmods.dev/badge/skills/notque/vexjoy-agent/plant-seed.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector 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 | $0.00016 | $0.01826 |
| Opus 5.5 | $0.00006 | $0.00730 |
| Sonnet 5.5 | $0.00003 | $0.00365 |
| Haiku 4.5 | $0.00002 | $0.00183 |
Grade A, and why
plant-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 25d 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.
How it starts
The opening of the file, as written. The whole thing — 216 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Plant Seed Skill
Overview
Capture forward-looking ideas with trigger conditions so they resurface at the right time. Seeds carry WHY (rationale) and WHEN (trigger), making them far more valuable than bare TODO comments.
Seeds are stored locally in .seeds/ (gitignored) and automatically surfaced during feature-lifecycle design phase when their trigger conditions match. This workflow is designed for deferred ideas only — if the user describes work that should happen now, suggest creating a task or issue instead.
Instructions
Phase 1: CAPTURE
Goal: Gather the idea, trigger condition, scope, and rationale from the user.
Key Constraint: This skill captures deferred ideas only. If the user describes something that should happen in the current session, suggest creating a task or issue instead. Planting a seed for immediate work means it never gets surfaced — it just gets forgotten in a different way.
Step 1: Understand the idea
Extract from the user's description:
- What (action): The specific thing to do when the time is right
- Why (rationale): The insight or observation that motivates this idea
- When (trigger): A human-readable string describing when this becomes relevant
If the user provides all three, proceed. If any are missing, ask:
For missing trigger condition:
When should this idea resurface? Describe the condition, e.g.:
- "when we add user accounts"
- "when performance optimization is needed"
- "when the API exceeds 10 endpoints"
For missing scope:
How big is this work? Small (< 1 hour), Medium (1-4 hours), or Large (4+ hours)?
For missing rationale:
Why does this matter? What's the insight behind this idea? (e.g., "Response times degrade linearly with DB calls per request -- at 10+ endpoints the shared query pattern becomes the bottleneck")
Step 2: Generate seed ID
Format: seed-YYYY-MM-DD-slug
- Date is today's date
- Slug is a short kebab-case summary of the action (3-5 words max)
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.
- 26d ago Changed · -167 lines · +4 tokens per session 3da4b59599ff
- 27d ago Changed 2300fdd11cc0
- 1mo ago First seen · 216 lines · 16 tokens per session scan A 6be866b9d12a
plant-seed is a skill published in the GitHub repository notque/vexjoy-agent (442 stars, last pushed today), licensed MIT. It adds 16 tokens to every session and 1,826 once invoked, about $0.0001 per session on Opus 5.5. 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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