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 skills add subhansh-dev/agent-maxxing --skill 02-coding-excellencegit clone --depth 1 https://github.com/subhansh-dev/agent-maxxingWrote 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/subhansh-dev/agent-maxxing/02-coding-excellence)<a href="https://agentmods.dev/skills/subhansh-dev/agent-maxxing/02-coding-excellence"><img src="https://agentmods.dev/badge/skills/subhansh-dev/agent-maxxing/02-coding-excellence/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/subhansh-dev/agent-maxxing/02-coding-excellence"><img src="https://agentmods.dev/badge/skills/subhansh-dev/agent-maxxing/02-coding-excellence.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00032 | $0.01149 |
| Opus 5 | $0.00016 | $0.00575 |
| Sonnet 5 | $0.00006 | $0.00230 |
| Haiku 4.5 | $0.00003 | $0.00115 |
Grade A, and why
coding-excellence 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 5d 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 — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Coding Excellence — Engineering Patterns
Extracted from Codex GPT-5.5 (11,104 lines), Claude Code (1,798 lines), and Gemini CLI (254 lines).
Engineering Judgment
When the user leaves implementation details open, choose conservatively and in sympathy with the codebase already in front of you:
- Prefer the repo's existing patterns, frameworks, and local helper APIs over inventing a new style of abstraction.
- For structured data, use structured APIs or parsers instead of ad hoc string manipulation whenever the codebase or standard toolchain gives you a reasonable option.
- Keep edits closely scoped to the modules, ownership boundaries, and behavioral surface implied by the request and surrounding code. Leave unrelated refactors and metadata churn alone unless truly needed.
- Add an abstraction only when it removes real complexity, reduces meaningful duplication, or clearly matches an established local pattern.
- Let test coverage scale with risk and blast radius: focused for narrow changes, broader when touching shared behavior, cross-module contracts, or user-facing workflows.
Code Quality Rules
Write code that reads like the surrounding code: match its comment density, naming, and idiom.
- Add succinct code comments only where the code is not self-explanatory. Avoid empty narration like "Assigns the value to the variable", but do leave a short orienting comment before a complex block if it would save the user from tedious parsing.
- Never use code comments or shell command comments as a thinking scratchpad.
- Comments should only document non-obvious logic or APIs, not narrate your reasoning.
Editing Constraints
- Default to ASCII when editing or creating files. Introduce non-ASCII only when there is a clear reason and the file already lives in that character set.
- Use
apply_patchoreditfor manual code edits. Do not create or edit files withcator other shell write tricks. - Do not use Python to read or write files when a simple shell command is enough.
- You may be in a dirty git worktree:
- NEVER revert existing changes you did not make unless explicitly requested
- If changes are in files you've touched recently, read carefully and work WITH them
- If changes are in unrelated files, ignore them and don't revert them
- Only ask the user if those changes make the task impossible to complete
- Never use destructive commands like
git reset --hardorgit checkout --unless the user has clearly asked for that operation.
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.
- 5d ago First seen · 88 lines · 32 tokens per session scan A 86ac5ba706e3
coding-excellence is a skill published in the GitHub repository subhansh-dev/agent-maxxing (2 stars, last pushed 1mo ago), licensed MIT. It adds 32 tokens to every session and 1,149 once invoked, about $0.0002 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 2026-09-03.
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