Borrowing it
Nothing to install: this file belongs to davidmatousek/tachi. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/davidmatousek/tachi/main/.claude/skills/code-execution-helper/SKILL.mdgit clone --depth 1 https://github.com/davidmatousek/tachiWrote 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/davidmatousek/tachi/code-execution-helper)<a href="https://agentmods.dev/skills/davidmatousek/tachi/code-execution-helper"><img src="https://agentmods.dev/badge/skills/davidmatousek/tachi/code-execution-helper/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/davidmatousek/tachi/code-execution-helper"><img src="https://agentmods.dev/badge/skills/davidmatousek/tachi/code-execution-helper.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00076 | $0.03305 |
| Opus 5.5 | $0.00030 | $0.01322 |
| Sonnet 5.5 | $0.00015 | $0.00661 |
| Haiku 4.5 | $0.00008 | $0.00331 |
Grade A, and why
code-execution-helper 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- code-execution-helper — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 410 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Execution Helper
This skill provides guidance for using code execution capabilities efficiently in Claude Code workflow agents. Code execution enables agents to perform parallel batch processing, conditional filtering, and data aggregation while dramatically reducing token consumption.
About Code Execution
Code execution allows agents to run TypeScript code in a sandboxed Deno runtime, enabling operations that would otherwise require loading massive amounts of data into context. By processing data in the execution environment and returning only filtered or aggregated results, agents can achieve 30-95% token reduction for high-value use cases.
Key Benefits
- Parallel batch processing - Scan 10+ files simultaneously instead of sequentially
- Conditional filtering - Return only relevant data (e.g., CRITICAL vulnerabilities only)
- Data aggregation - Summarize patterns across multiple sources
- Token efficiency - Process large datasets without context window limits
- Quota awareness - Check API limits before execution to prevent failures
When to Use Code Execution
Use code execution when tasks meet these criteria:
- Multiple operations: More than 5 files, API calls, or validation checks
- Large datasets: Results exceed 10,000 tokens if loaded into context
- Conditional logic: Need to filter, aggregate, or transform data before returning
- Parallel processing: Operations can run simultaneously for faster execution
- Token efficiency: Reducing context usage is important for the workflow
When NOT to Use Code Execution
Avoid code execution for:
- Single operations: One file scan, one API call, simple queries
- Small datasets: Results under 2,000 tokens
- Direct responses: User needs raw data without filtering
- Simple queries: Questions answerable with existing tools
- Debugging code execution itself: Use direct tools to avoid recursion
Decision Criteria
To determine whether to use code execution, apply these thresholds:
What ships with it
6 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 · 410 lines · 76 tokens per session scan A 31e68a85f993
code-execution-helper is a skill published in the GitHub repository davidmatousek/tachi (94 stars, last pushed 4d ago), licensed Apache-2.0. It adds 76 tokens to every session and 3,305 once invoked, about $0.0003 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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