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 animicaorg/animica-mcp --skill animica-deploygit clone --depth 1 https://github.com/animicaorg/animica-mcpWrote 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/animicaorg/animica-mcp/animica-deploy)<a href="https://agentmods.dev/skills/animicaorg/animica-mcp/animica-deploy"><img src="https://agentmods.dev/badge/skills/animicaorg/animica-mcp/animica-deploy/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/animicaorg/animica-mcp/animica-deploy"><img src="https://agentmods.dev/badge/skills/animicaorg/animica-mcp/animica-deploy.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00058 | $0.00973 |
| Opus 5 | $0.00029 | $0.00487 |
| Sonnet 5 | $0.00012 | $0.00195 |
| Haiku 4.5 | $0.00006 | $0.00097 |
Grade A, and why
animica-deploy 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 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s -X POST https://animica.org/deploy/api/preview \ How it starts
The opening of the file, as written. The whole thing — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deploy on Animica
Two distinct products:
A. Website + AI — animica.org/deploy ($20 one-time)
https://animica.org/deploy/ adds an AI assistant to an existing website. USD 20 one-time via PayPal — a human must complete the payment; an agent can drive the preview.
Preview (agent-drivable, no auth)
curl -s -X POST https://animica.org/deploy/api/preview \
-H 'Content-Type: application/json' \
-d '{"url":"https://example.com"}'
# -> {"siteName":"Example Domain","origin":"https://example.com","pagesDiscovered":1,
# "topics":[],"samplePages":[{"url":"https://example.com/","title":"Example Domain"}],
# "normalizedUrl":"https://example.com/"}
Missing/invalid url returns 400 {"error":"url_required"}.
Checkout
POST https://animica.org/deploy/api/checkout (same {"url": …} shape) starts the PayPal flow. Hand the resulting checkout to the human — agents must not attempt to complete payment.
B. Python cloud — animica.dev/api/cloud
Deploy a Python function to a public HTTPS endpoint with metered execution billed in ANM; the platform takes 20%, the deployer keeps the rest. Docs: https://animica.dev/docs/cloud.
Auth: API key prefixed anm_mkt_ (created by a human in the animica.dev Developer Center) or a signed-in browser session.
1. Write a function (one file, one module-level entrypoint)
# handler.py — request = parsed JSON body (POST) or query params (GET); return JSON-serializable
def main(request):
name = str(request.get("name", "world"))[:80] if isinstance(request, dict) else "world"
return {"greeting": f"Hello, {name}!"}
2. Create the function
curl -s https://animica.dev/api/cloud/v1/functions \
-H "authorization: Bearer $ANM_KEY" \
-H 'content-type: application/json' \
-d '{"slug": "hello", "name": "Hello", "timeoutMs": 10000, "memoryMb": 128}'
# -> { "function": { "id": "…", "slug": "hello", "status": "DRAFT", … } }
3. Deploy version 1
curl -s https://animica.dev/api/cloud/v1/functions/$FUNCTION_ID/versions \
-H "authorization: Bearer $ANM_KEY" \
-H 'content-type: application/json' \
-d "$(python3 -c 'import json; print(json.dumps({"source": open("handler.py").read(), "entrypoint": "main"}))')"
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 · 84 lines · 58 tokens per session scan A 97f3e18e767a
animica-deploy is a skill published in the GitHub repository animicaorg/animica-mcp (0 stars, last pushed 26d ago), licensed Apache-2.0. It adds 58 tokens to every session and 973 once invoked, about $0.0003 per session on Opus 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 2026-08-31.
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