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 commands/deeleeramone/pywry/scaffoldgit 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 | $0.00024 | $0.00408 |
| Opus 5 | $0.00012 | $0.00204 |
| Sonnet 5 | $0.00005 | $0.00082 |
| Haiku 4.5 | $0.00002 | $0.00041 |
Grade A, and why
scaffold 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.
What it actually says
Scaffold a new PyWry app in a fresh directory named by the first positional argument $ARGUMENTS. If no argument is given, ask the user for a name.
Before writing any files, call the get_skills MCP tool with the topic that matches --kind (default widget → skill component_reference, chat → chat, tvchart → tvchart, dashboard → data_visualization). Read the returned skill text before choosing the template.
Then create the following files in ./<app-name>/:
main.py— a runnable PyWry app usingPyWry().show*(...)appropriate to--kind. Keep it under 40 lines. Use headless‑friendly patterns (no hard‑codedblock()call at module import level).pyproject.toml— minimal, pinned topywry[mcp]>=2.0.0rc7. Use the user's Python version.README.md— one paragraph describing the app and apython main.pyquick start..gitignore— standard Python entries (__pycache__/,*.pyc,.venv/).
After writing files:
- Run
ruff formatonmain.py - Print the directory listing
- Tell the user:
cd <app-name> && pip install -e . && PYWRY_HEADLESS=1 python main.pyto run headlessly, or dropPYWRY_HEADLESS=1to see the native window
Do not install the package or run the app automatically. The user should review the generated code first.
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 · 23 lines · 24 tokens per session scan A 03eca212e4aa
scaffold is a command published in the GitHub repository deeleeramone/PyWry (93 stars, last pushed 9d ago), licensed Apache-2.0. It adds 24 tokens to every session and 408 once invoked, about $0.0001 per session on Opus 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 2026-08-30.
Other commands, from other repositories
validate_changed_docstrings
Validates Python docstrings in all uncommitted changed files using Sphinx parsing.
autobot-stop
Stop an autobot session (kill tmux and dev environment, but keep the worktree).
autobot-result
Print the most recent result.md for an autobot session, so the user can see how a bot is doing without attaching to its tmux session.
ci-report
Generate a CI failure report for PR $PRNUMORURL (or current branch if no argument given).
autobot-list
List all autobot sessions with status information.
implement-python
Senior Python engineer implementation command. Launches a background agent with full Python development capabilities and access to the mastering-python-skill reference materials.