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/i9wa4/dotfiles/programmingnpx skills add i9wa4/dotfiles --skill programminggit clone --depth 1 https://github.com/i9wa4/dotfilesWhat 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 | $0.00061 | $0.00476 |
| Opus 5 | $0.00030 | $0.00238 |
| Sonnet 5 | $0.00012 | $0.00095 |
| Haiku 4.5 | $0.00006 | $0.00048 |
Grade A, and why
programming 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
Programming
Owns repo-local implementation guidance and debugging. Prefer a narrower domain skill when one exists.
1. Scope
- Bash scripts and shell command design.
- Python utility edits, local execution, and general Python quality: type hints, pytest, uv/ruff/pyright tooling, Jupyter notebooks.
- Nix package workflow, especially fetcher hash acquisition.
- Terraform infrastructure code development, plan review, and Checkov security/compliance scanning.
- Markdown authoring and formatting rules.
- Red-Green-Refactor and Tidy First implementation loops.
- Systematic debugging: reproducers, working-pattern comparison, root cause.
Out of scope:
- Agent harness runtime, Home Manager agent config, hooks, postman routing, or
installed agent outputs; use
dotfiles. - GitHub issue, PR, review, or public-surface mechanics; use
collaboration. - Data-platform or diagramming workflows; use their target skills.
2. Workflow
- Inspect relevant files, repo conventions, and
git status. - Select the focused reference below before changing files.
- Keep structural and behavioral edits separate when practical.
- Run the fastest focused check during iteration, then the nearest repo validation surface before reporting success.
- Report changed files, verification, residual Waza findings, and remaining risk.
3. References
What ships with it
12 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.
- evals/eval.yaml 508 B
- evals/tasks/negative-trigger-1.yaml 408 B
- evals/tasks/positive-trigger-1.yaml 436 B
- evals/tasks/positive-trigger-2.yaml 397 B
- references/bash-scripting.md 1.0 KB
- references/markdown-authoring.md 580 B
- references/nix-package-workflow.md 798 B
- references/python-development.md 817 B
- references/python-quality.md 1.5 KB
- references/systematic-debugging.md 2.6 KB
- references/tdd-tidy-first.md 1.4 KB
- references/terraform-development.md 5.3 KB
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 · 54 lines · 61 tokens per session scan A f0d5b485d99c
programming is a skill published in the GitHub repository i9wa4/dotfiles (11 stars, last pushed 2d ago), licensed MIT. It adds 61 tokens to every session and 476 once invoked, about $0.0003 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 skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
babysit-pr
Babysit a GitHub pull request after creation by continuously polling review comments, CI checks/workflow runs, and mergeability state until the PR is merged/closed or user help is required. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and keep…
imagegen
Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output…
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…