Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/crypdick/pynchynpx agentmods add skills/crypdick/pynchy/pynchy-devWrote 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/crypdick/pynchy/pynchy-dev)<a href="https://agentmods.dev/skills/crypdick/pynchy/pynchy-dev"><img src="https://agentmods.dev/badge/skills/crypdick/pynchy/pynchy-dev/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/crypdick/pynchy/pynchy-dev"><img src="https://agentmods.dev/badge/skills/crypdick/pynchy/pynchy-dev.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 MCP Rug Pull · line 21 uvx/uv tool run commands without ==version create a rug-pull risk.Fix: Pin the version: uvx package-name==1.2.3
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 | $0.00079 | $0.01227 |
| Opus 5.5 | $0.00032 | $0.00491 |
| Sonnet 5.5 | $0.00016 | $0.00245 |
| Haiku 4.5 | $0.00008 | $0.00123 |
Grade A, and why
Pynchy Development 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 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.
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 — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pynchy Development
Run commands directly—don't tell the user to run them.
Am I on pynchy?
Check hostname and compare it with the deployment-specific live host from local memory, environment, or the operator. If you are on that host, access services at localhost. Otherwise, reach Pynchy over SSH or Tailscale using that configured host.
Commands
uv run pynchy # Run the app
uv run pytest tests/ # Run tests
uv run ruff check --fix src/ # Lint + autofix
uv run ruff format src/ # Format
uvx prek==0.4.10 run --all-files # Run all repository hooks
./src/pynchy/agent/build.sh # Rebuild agent container
Managed worktrees and optional runtimes
Use new-feature create <slug> --no-agent from the control checkout before any source or
documentation edit. Work in the resulting .worktrees/<slug> directory; direct edits on the
target branch are blocked. Setup installs dependencies but does not start a runtime. Start
an isolated Pynchy runtime only when interactive diagnosis needs one.
See the feature-runtime workflow for create, merge,
restart, and teardown commands. Do not use raw git worktree commands for managed features.
Install or verify its host dependencies with ./scripts/install_new_feature_dependencies.py.
Private overlay edits belong in the independent personalization repository's own managed worktree, not in the public Pynchy worktree. See editing personalization.
Quality checks
Keep correctness, security, architecture, and coverage checks blocking. The comment-language check is advisory. Host beartype violations warn in production and fail tests; fix the contract or test double instead of suppressing violations. Host annotations used by beartype need runtime imports; Ruff's host configuration handles this without per-import exemptions. Agent-runner uses its own lint config.
Run focused checks while editing a coherent change. The managed merge owns the full verification sequence; repeat it only after changes or unresolved failures.
What ships with it
4 files 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 3f34c8dc9d34
- 1mo ago Changed · +18 lines 16c672d09dfe
- 1mo ago First seen · 78 lines · 79 tokens per session scan A 6499cd93393a
Pynchy Development is a skill published in the GitHub repository crypdick/pynchy (10 stars, last pushed 1mo ago), licensed MIT. It adds 79 tokens to every session and 1,227 once invoked, about $0.0003 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 2026-08-31.
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