agentmods.dev

code_interpreter

A tool for running Python code in an isolated environment. Python is a programming language often used for calculations, data processing, file-format conversion, and preparing chart data.

In plain words
What is it for?
Use it for data analysis, numerical calculations, JSON conversion, and generating data for charts. It does not create charts itself.
Why use it?
It handles tasks where the answer must be calculated or produced by actually running code, rather than guessed from text.

Skill for Claude CodeCodex

135 19d ago A scan 42 tokens original MIT
View the source file wanmol/goal-flow
Install

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.

agentmods
npx agentmods add skills/wanmol/goal-flow/code_interpreter
Any agent
npx skills add wanmol/goal-flow --skill code_interpreter
Clone the repo
git clone --depth 1 https://github.com/wanmol/goal-flow

Made for: Claude Code, Codex.

Per session 42 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 308 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00042 $0.00308
Opus 5 $0.00021 $0.00154
Sonnet 5 $0.00008 $0.00062
Haiku 4.5 $0.00004 $0.00031

Measured 2d ago against content hash 1ccd5ffd4cc2, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

code_interpreter 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.

The scan reads SKILL.md. This mod also ships 3 executable files (__init__.py, scripts/__init__.py, scripts/run.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

src/agent_kit/skills/builtin/code_interpreter/SKILL.md · 39 lines

What it actually says

code_interpreter

通过远端 dify-sandbox 服务执行 Python 代码并返回 stdout。

适用场景：

  • 数据分析与统计计算（pandas / numpy）
  • 数值计算与复杂公式（涉及循环、条件、多步骤）
  • 格式转换（JSON 解析、数据整理）
  • 图表数据生成（只输出数据，不出图）
  • 任何需要执行代码才能得出结果的任务

约束：

  • 必须用 print() 输出最终结果，否则看不到返回。
  • 禁止使用绘图库（matplotlib / seaborn / plotly 等），如需图表请只输出数据由上层渲染。
  • 无文件系统 / 网络持久化保证。
Files

What ships with it

3 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.

Changes

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.

  1. 2d ago First seen · 39 lines · 42 tokens per session scan A 1ccd5ffd4cc2

Subscribe to this mod's changes

code_interpreter is a skill published in the GitHub repository wanmol/goal-flow (135 stars, last pushed 19d ago), licensed MIT. It adds 42 tokens to every session and 308 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 2026-08-30.

Data and AILanguagesagentagenticagentic-aiagentic-engineeringaicalculationcodedata-analysisdeepage
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