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/ericwang915/pythonclaw/skill_creatornpx skills add ericwang915/PythonClaw --skill skill_creatorgit clone --depth 1 https://github.com/ericwang915/PythonClawWhat 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 | $0.00065 | $0.00630 |
| Opus 5 | $0.00032 | $0.00315 |
| Sonnet 5 | $0.00013 | $0.00126 |
| Haiku 4.5 | $0.00006 | $0.00063 |
Grade A, and why
skill_creator 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.
How it starts
The opening of the file, as written. The whole thing — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill Creator
When to Use
- The user asks for something no installed skill covers
- An existing skill is too limited and needs a better replacement
- A recurring task would benefit from a dedicated, reusable skill
When NOT to Use
- One-off tasks that existing tools can handle (e.g.,
run_commandfor shell) - Skills too specific to be reused — generalize first
- Don't hardcode user-specific values (names, URLs, topics) — use parameters
Setup
Uses the create_skill tool. No API keys or external setup required.
Usage/Commands
- Analyze the gap: identify what capability is missing
- Plan the skill: name, category, scripts, pip dependencies
- Call
create_skillwith:name— short, snake_case (e.g.,pdf_summarizer)description— one-line summaryinstructions— full Markdown bodycategory— e.g.,data,dev,web,automationresources— dict mapping filenames to source codedependencies— list of pip packages
- Activate:
use_skill(skill_name="<name>") - Run it: follow the loaded instructions
Design Principles
- Generic over specific — parameterize everything; avoid hardcoded topics/recipients
- Single responsibility — one skill, one purpose
- Parameterized — use CLI args, not hardcoded values
- Config-driven credentials — read from
pythonclaw.jsonunderskills.<name> - Minimal dependencies — only add pip packages when truly needed
- Reusable — ask: "Would this help someone with a different task?"
SKILL.md Body Template
## Instructions
<Clear explanation and when to use.>
### Prerequisites
<Setup, API keys if needed>
### Usage
1. <steps>
2. Call: `python context/skills/<category>/<name>/<script>.py <args>`
3. <interpret results>
### Examples
**Example:** <typical use case>
## Resources
| File | Description |
|------|-------------|
| script.py | <what it does> |
Notes
- Design for reuse: generalize queries, recipients, URLs
- Write production-quality Python with error handling and docstrings
- After creation, call
use_skillto load the new instructions before running
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 · 80 lines · 65 tokens per session scan A 47d78778e1c6
skill_creator is a skill published in the GitHub repository ericwang915/PythonClaw (41 stars, last pushed 24d ago), licensed MIT. It adds 65 tokens to every session and 630 once invoked, about $0.0003 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.
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