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 gradion-ai/ipybox --skill codeactgit clone --depth 1 https://github.com/gradion-ai/ipyboxWrote 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/gradion-ai/ipybox/codeact)<a href="https://agentmods.dev/skills/gradion-ai/ipybox/codeact"><img src="https://agentmods.dev/badge/skills/gradion-ai/ipybox/codeact/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/gradion-ai/ipybox/codeact"><img src="https://agentmods.dev/badge/skills/gradion-ai/ipybox/codeact.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 | $0.00030 | $0.00495 |
| Opus 5.5 | $0.00012 | $0.00198 |
| Sonnet 5.5 | $0.00006 | $0.00099 |
| Haiku 4.5 | $0.00003 | $0.00049 |
Grade A, and why
codeact 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 1mo 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 — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Use Python tools to perform tasks.
You must use the execute_ipython_cell tool of the ipybox MCP server for executing Python code.
All operations must follow the tool usage restrictions and workflows defined below.
Tool Directories
The gentools/ and mcptools/ directories are in the working directory shown in your <env> block. All paths are relative to the working directory, NOT to this skill's base directory.
Tool Usage Restrictions
You are restricted to these tools only:
Python Tools
- Functions in
mcptools/<category>/<tool>.py(userun_parsedif defined, otherwiserun) - Functions in
gentools/<category>/<tool>/api.py
ipybox MCP Server Tools
execute_ipython_cell- Execute Python codereset- Reset the IPython kernel
Claude Code Filesystem Tools
- All filesystem tools for reading, writing files, and listing directories.
Workflow
1. Python Tool Selection
- List available categories in
gentools/andmcptools/ - List available tools in relevant categories
- Read tool files to understand interfaces and parameters.
2. Python Tool Priority
- Search
gentoolspackage first - If not found, search
mcptoolspackage - If no appropriate tool exists, generate custom code
3. Code Generation and Python Tool Chaining
- Generate code that uses selected Python tools as argument for
execute_ipython_cell. - Chain Python tools in the generated code if the structured output of one tool can be used as input for another tool.
4. Code Execution
- Use the
execute_ipython_cellfor Python code execution - Print only required information, not intermediate results
- Store intermediate results in variables
Output Parsers
When generating output parsers for Python tools in the mcptools package, see references/output-parsers.md.
Saving Code Actions
To save executed code as a reusable gentools tool, see references/saving-codeacts.md.
What ships with it
2 files 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.
- 1mo ago First seen · 66 lines · 30 tokens per session scan A 2cf1bf4a7c39
codeact is a skill published in the GitHub repository gradion-ai/ipybox (76 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 30 tokens to every session and 495 once invoked, about $0.0001 per session on Opus 5.5. 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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