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 agentmods add skills/deeleeramone/pywry/deploynpx skills add deeleeramone/PyWry --skill deploygit clone --depth 1 https://github.com/deeleeramone/PyWryWhat 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 | $0.00000 | $0.01658 |
| Opus 5 | $0.00000 | $0.00829 |
| Sonnet 5 | $0.00000 | $0.00332 |
| Haiku 4.5 | $0.00000 | $0.00166 |
Grade A, and why
deploy 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 2d 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 — 254 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Production Deploy Mode
CRITICAL: This mode is for production servers serving multiple concurrent users. Widgets are stateless. State lives externally. Scale horizontally.
What Deploy Mode IS
You're creating widgets for a production SSE server with:
- Multiple concurrent users/sessions
- Stateless widget creation
- Horizontal scaling support
- Persistent widget URLs
Architecture
┌─────────────────┐
│ Load Balancer │
└────────┬────────┘
│
┌────────────────────────┼────────────────────────┐
│ │ │
▼ ▼ ▼
┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
│ PyWry Server │ │ PyWry Server │ │ PyWry Server │
│ (SSE #1) │ │ (SSE #2) │ │ (SSE #3) │
└─────────────────┘ └─────────────────┘ └─────────────────┘
│ │ │
└────────────────────────┼────────────────────────┘
│
▼
┌───────────────────────┐
│ Shared State Store │
│ (Redis / Database) │
└───────────────────────┘
Key Principles
Widgets Are Stateless
- Widget instances don't persist server state
- Store state externally (Redis, database, etc.)
- Any server can handle any widget update
Session Management
- Each user gets a unique widget_id
- Map widget_id to user session externally
- Implement timeouts and cleanup
Horizontal Scaling
- Servers behind load balancer
- SSE connections are per-server (sticky sessions may help)
- Widget operations are idempotent
Best Practices
1. Widget IDs - Use Meaningful IDs
# Include user/session info in widget_id
widget_id = f"user_{user_id}_dashboard"
# Or use session-scoped IDs
widget_id = f"session_{session_id}_chart"
# This makes debugging and monitoring easier
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.
- 2d ago First seen · 254 lines · 0 tokens per session scan A 9225a7f0a933
deploy is a skill published in the GitHub repository deeleeramone/PyWry (93 stars, last pushed 8d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 1,658 tokens. 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.
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