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/qte77/claude-code-plugins/implementing-pythonnpx skills add qte77/claude-code-plugins --skill implementing-pythongit clone --depth 1 https://github.com/qte77/claude-code-pluginsWrote 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/qte77/claude-code-plugins/implementing-python)<a href="https://agentmods.dev/skills/qte77/claude-code-plugins/implementing-python"><img src="https://agentmods.dev/badge/skills/qte77/claude-code-plugins/implementing-python.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 | $0.00036 | $0.00412 |
| Opus 5 | $0.00018 | $0.00206 |
| Sonnet 5 | $0.00007 | $0.00082 |
| Haiku 4.5 | $0.00004 | $0.00041 |
Grade A, and why
implementing-python 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 today.
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
Python Implementation
Target: $ARGUMENTS
Creates focused, streamlined Python implementations following architect specifications exactly. No over-engineering.
Python Standards
See references/python-best-practices.md for comprehensive Python guidelines.
Workflow
- Read architect specifications from provided documents
- Validate scope - Simple (100-200 lines) vs Complex (500+ lines)
- Study existing patterns in
src/structure - Implement minimal solution matching stated functionality
- Create focused tests matching task complexity
- Run
make validateand fix all issues
Implementation Strategy
Simple Tasks: Minimal functions, basic error handling, lightweight dependencies, focused tests
Complex Tasks: Class-based architecture, comprehensive validation, necessary dependencies, full test coverage
Always: Use existing project patterns, pass make validate
Output Standards
Simple Tasks: Minimal Python functions with basic type hints Complex Tasks: Complete modules with comprehensive testing All outputs: Concise, streamlined, no unnecessary complexity
Quality Checks
Before completing any task:
make validate
All type checks, linting, and tests must pass.
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.
- today First seen · 58 lines · 36 tokens per session scan A 36854188783e
implementing-python is a skill published in the GitHub repository qte77/claude-code-plugins (2 stars, last pushed 4d ago), licensed Apache-2.0. It adds 36 tokens to every session and 412 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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