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 ai-ecoverse/slicc --skill dipsgit clone --depth 1 https://github.com/ai-ecoverse/sliccWrote 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/ai-ecoverse/slicc/dips)<a href="https://agentmods.dev/skills/ai-ecoverse/slicc/dips"><img src="https://agentmods.dev/badge/skills/ai-ecoverse/slicc/dips/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/ai-ecoverse/slicc/dips"><img src="https://agentmods.dev/badge/skills/ai-ecoverse/slicc/dips.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, 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 Agent Snooping · line 121 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00129 | $0.02466 |
| Opus 5.5 | $0.00052 | $0.00986 |
| Sonnet 5.5 | $0.00026 | $0.00493 |
| Haiku 4.5 | $0.00013 | $0.00247 |
Grade A, and why
dips scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
result=$(agent "$TMPDIR" "curl,jq" "Fetch <url>, return field 'price' as a number.") How it starts
The opening of the file, as written. The whole thing — 167 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Dips
Dips are inline shtml code blocks in chat that hydrate into sandboxed interactive widgets. Ephemeral — no state persistence, no readFile. Only slicc.lick(event) is available for agent communication; always pack payloads as { action, data: { ... } } for a predictable shape on the cone side.
Use them generously. A dip is the right answer any time a response could benefit from visualization, interaction, or a moment of delight. Don't reserve them for "complex" tasks — a slider that lets the user feel a number, a chart that beats a paragraph of stats, a button that's faster than typing "yes" all earn their keep.
| Reach for a dip when … | Reach for a sprinkle when … |
|---|---|
| The answer would land better as a widget than as prose | The user needs a persistent dashboard / editor / multi-page app |
| The user is choosing, confirming, or tuning a value | The UI must survive across turns or sessions |
| You want a chart, animation, or interactive demo | You need readFile, screenshot, or any persistent state |
| The result deserves a bit of fun | The interaction is long-running |
For a gallery of 10 ready-to-adapt patterns (drag-on-canvas, slider→DOM reflow, paste→tree, ...) read the companion file: read_file /workspace/skills/dips/patterns.md.
Card structure
Always wrap interactive content in .sprinkle-action-card for visual containment. Don't output bare HTML — cards need a visible boundary.
<div class="sprinkle-action-card">
<div class="sprinkle-action-card__header">Title <span class="sprinkle-badge sprinkle-badge--notice">Status</span></div>
<div class="sprinkle-action-card__body">Description text</div>
<div class="sprinkle-action-card__actions">
<button class="sprinkle-btn sprinkle-btn--secondary" onclick="slicc.lick('cancel')">Cancel</button>
<button class="sprinkle-btn sprinkle-btn--primary" onclick="slicc.lick('confirm')">Confirm</button>
</div>
</div>
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago Changed 762943219140
- 1mo ago First seen · 167 lines · 129 tokens per session scan A 95b039b6d1f0
dips is a skill published in the GitHub repository ai-ecoverse/slicc (34 stars, last pushed 2d ago), licensed Apache-2.0. It adds 129 tokens to every session and 2,466 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-05.
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