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/dds-solutions/ai-tadpole-os/clean-codenpx skills add DDS-Solutions/AI-TadPole-OS --skill clean-codegit clone --depth 1 https://github.com/DDS-Solutions/AI-TadPole-OSWrote 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/dds-solutions/ai-tadpole-os/clean-code)<a href="https://agentmods.dev/skills/dds-solutions/ai-tadpole-os/clean-code"><img src="https://agentmods.dev/badge/skills/dds-solutions/ai-tadpole-os/clean-code.svg" alt="Measured on agentmods" 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 | $0.00022 | $0.00564 |
| Opus 5 | $0.00011 | $0.00282 |
| Sonnet 5 | $0.00004 | $0.00113 |
| Haiku 4.5 | $0.00002 | $0.00056 |
Grade A, and why
clean-code 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 4d 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
[!IMPORTANT] AI Context & Knowledge Heritage
- Subsystem: Agent Skills Registry / clean-code
- Architecture:
@docs ARCHITECTURE:Documentation- Failure Path: Information drift, legacy terminology, or documentation mismatch.
- Observability: Traceability via
execution/parity_guard.py([SKILL])
Clean Code — Pragmatic Engineering Standards
Philosophy: Be concise, direct, and solution-focused. Code is written for humans to read and machines to execute.
🎯 Progressive Disclosure & L3 Reference Index
Read REQUIRED core coding standards below; consult deep L3 Reference Guides on demand:
| L3 Reference Guide | Purpose | Trigger / When to Load |
|---|---|---|
references/refactoring_and_git_standards.md |
Testing pyramid (70/20/10), Git commit standards, refactoring checklists | Pull requests & unit test coverage planning |
📐 1. Core Engineering Principles
| Principle | Meaning & Practical Rule |
|---|---|
| Single Responsibility (SRP) | Each function or struct does ONE thing well. |
| Guard Clauses | Return early for edge cases; avoid deep if / else nesting. |
| Colocation | Keep related logic, types, and unit tests physically close to their usage. |
| Self-Documenting Code | Reveal intent through precise names (is_active, get_user_by_id). Avoid redundant inline comments. |
🚫 2. Critical Anti-Patterns to Avoid
- No God Objects: Never let a single file or function grow beyond 500 lines. Decompose into focused modules.
- No
utils.tsDumps: Put functions in their respective domain namespaces instead of generic grab-bag files. - No Magic Numbers / Strings: Define named constants (
MAX_RETRIES,DEFAULT_TIMEOUT_SECS) at file headers. - No Swallowed Errors: Always handle or re-wrap errors with contextual domain traces.
🛠️ 3. Verification Gate
# Verify syntax, formatting, and doc parity
python execution/parity_guard.py .
What ships with it
1 file 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.
- 4d ago First seen · 58 lines · 22 tokens per session scan A bb8829f1b4e0
clean-code is a skill published in the GitHub repository DDS-Solutions/AI-TadPole-OS (8 stars, last pushed today), licensed MIT. It adds 22 tokens to every session and 564 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 2026-08-31.
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