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/kissgyorgy/coding-agents/pythonnpx skills add kissgyorgy/coding-agents --skill pythongit clone --depth 1 https://github.com/kissgyorgy/coding-agentsWhat 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 | $0.00023 | $0.00537 |
| Opus 5 | $0.00012 | $0.00269 |
| Sonnet 5 | $0.00005 | $0.00107 |
| Haiku 4.5 | $0.00002 | $0.00054 |
Grade A, and why
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 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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 · 45 lines · 23 tokens per session scan A b4e01d0e357e
python is a skill published in the GitHub repository kissgyorgy/coding-agents (12 stars, last pushed 2d ago), with no licence file. It adds 23 tokens to every session and 537 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
agent-rig-system
A rig is a collection of riglets that provide knowledge and tools for AI agents. Rigs and riglets are packaged as Nix flake outputs, so they can both be used inside the project defining them and by other projects depending on it.
riglet-creator
Creating effective riglets means writing knowledge (SKILL.md) that agents will rely on. This guide focuses on how to write high-quality documentation for riglets, organized efficiently.
nix-module-system
Practical knowledge about lib.evalModules that's hard to find in official docs.
code-search
Fast, efficient utilities for searching code and browsing file hierarchies.
technical-writing
Layered technical-writing standard: Diátaxis structure, Google developer style sentences, STE instruction rules, Global English syntax. Use for /technical-writing or when writing or reviewing docs, RFCs, readmes, PR descriptions, or commit messages.
teach
Explain a body of work plainly so a person actually understands it. Runs the how and why skills and weaves what they find into one clear explanation. Use for 'teach me this', 'help me really understand X', 'explain this change or subsystem to me'.