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/j-morgan6/elixir-phoenix-guide/code-qualitynpx skills add j-morgan6/elixir-phoenix-guide --skill code-qualitygit clone --depth 1 https://github.com/j-morgan6/elixir-phoenix-guideWhat 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 | $0.00025 | $0.01296 |
| Opus 5 | $0.00013 | $0.00648 |
| Sonnet 5 | $0.00005 | $0.00259 |
| Haiku 4.5 | $0.00003 | $0.00130 |
Grade A, and why
code-quality 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 3d 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 — 180 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Quality Automation
Automated detection of code quality issues in Elixir projects. These checks run automatically via hooks when files are written, and can be run on-demand for full project analysis.
RULES — Follow these with no exceptions
- Duplicated functions must be extracted — when 2+ modules share >70% identical function implementations, create a shared module
- Functions must stay below ABC complexity 30 — break complex functions into smaller helpers with single responsibilities
- Unused private functions must be removed — dead code increases maintenance burden and confusion
- Duplicated templates must become components — when 2+ HEEx files share >40% identical markup, extract to a function component
- Run full analysis before major refactors — use
run_analysis.shto establish a baseline before and after - Address duplication before complexity — extracting shared code often reduces complexity as a side effect
- Prefer composition over inheritance — extract shared functions into modules imported/used where needed, not into base modules
What Gets Detected
Code Duplication
Detects when the same function appears in multiple modules with >70% body similarity.
How it works: AST-based analysis parses function bodies and compares them using trigram similarity. Functions with the same name, arity, and similar bodies are flagged.
Example output:
Duplication Detected
Function `format_time/1` (85% similar)
lib/app_web/live/cycle_time.ex:45
lib/app_web/live/lead_time.ex:52
Suggestion: Extract to a shared module
How to fix:
# Create: lib/app_web/live/helpers.ex
defmodule AppWeb.Live.Helpers do
def format_time(%Decimal{} = seconds) do
seconds |> Decimal.to_float() |> format_time()
end
def format_time(seconds) when is_number(seconds) do
# shared formatting logic
end
end
# In each LiveView:
import AppWeb.Live.Helpers, only: [format_time: 1]
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.
- 3d ago First seen · 180 lines · 25 tokens per session scan A 75b090d227fe
code-quality is a skill published in the GitHub repository j-morgan6/elixir-phoenix-guide (156 stars, last pushed 1mo ago), licensed MIT. It adds 25 tokens to every session and 1,296 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 skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
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…