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/firstp1ck/pi-coding-agent-forge/code-qualitynpx skills add Firstp1ck/pi-coding-agent-forge --skill code-qualitygit clone --depth 1 https://github.com/Firstp1ck/pi-coding-agent-forgeWhat 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 | $0.00049 | $0.01832 |
| Opus 5 | $0.00024 | $0.00916 |
| Sonnet 5 | $0.00010 | $0.00366 |
| Haiku 4.5 | $0.00005 | $0.00183 |
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 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.
This is a copy
89% identical to code-quality — 25 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 245 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Quality
Structured code review and quality enforcement across the user's tech stacks. Checklists, linting strategies, and metrics to keep codebases healthy.
Quick Start
Run a Code Quality Check
- Run static analysis: Linters, type checkers, formatters
- Review against checklist: Language-specific items below
- Check complexity metrics: Cyclomatic < 25, data flow < 25
- Report findings: Structured output with severity and recommendations
Linting Configurations
Rust — Clippy Config
the user's standard clippy configuration (in Cargo.toml or .clippy.toml):
[lints.clippy]
cognitive_complexity = "warn"
pedantic = { level = "deny", priority = -1 }
nursery = { level = "deny", priority = -1 }
unwrap_used = "deny"
Standard commands:
cargo fmt
cargo clippy --all-targets --all-features -- -D warnings
cargo check
cargo test -- --test-threads=1
Key rules to enforce:
- No
.unwrap()in non-test code (use?or.expect("reason")) - All public items have rustdoc (
#[warn(missing_docs)]) #[must_use]on functions that return values that should be checked- When using
#[allow(...)], always add a comment explaining why - If no good explanation exists for
#[allow(...)], fix the issue instead
TypeScript — ESLint + Strict Mode
Recommended tsconfig.json strictness:
{
"compilerOptions": {
"strict": true,
"noUncheckedIndexedAccess": true,
"noImplicitReturns": true,
"noFallthroughCasesInSwitch": true,
"exactOptionalPropertyTypes": true
}
}
Key rules to enforce:
- No
any— useunknownand type guards instead - No
// @ts-ignore— fix the type issue or use// @ts-expect-errorwith explanation - Prefer
constoverlet, never usevar - Use discriminated unions for state modeling
- Explicit return types on exported functions
Python — Ruff + Mypy
Recommended pyproject.toml:
[tool.ruff]
target-version = "py312"
line-length = 88
[tool.ruff.lint]
select = ["E", "F", "W", "I", "N", "UP", "ANN", "B", "A", "C4", "DTZ", "ISC", "PIE", "PT", "RET", "SIM", "TCH", "ARG", "PTH", "ERA"]
[tool.mypy]
strict = true
warn_return_any = true
warn_unreachable = true
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 · 245 lines · 49 tokens per session scan A acc38c1adc9c
code-quality is a skill published in the GitHub repository Firstp1ck/pi-coding-agent-forge (74 stars, last pushed 2d ago), licensed MIT. It adds 49 tokens to every session and 1,832 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 89% identical to code-quality, differing in 25 lines, and is treated as a copy.
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