openai-function-calling-tools: openai function calling tools for JS/TS

by JohannLai · LLM Plugin · ★ 313

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install openai-function-calling-tools

npm install openai-function-calling-tools

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 68/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

function-callingfunctionsjavascriptopenaiopenai-apitools

Quick Facts

Stars313
Forks28
LanguageTypeScript
CategoryLLM Plugin
LicenseMIT
Quality Score68/100
Open Issues4
Last Updated2024-01-30
Created2023-06-16
Platformsnode
Est. Tokens~29k

About openai-function-calling-tools

OpenAI Function calling tools OpenAI Function calling tools OpenAI Function calling tools is a repository that offers a set of tools to help you easy to build a function calling model with OpenAI API. More information about function calling Sample: https://chatFn.io 🪓 Tools The repo provides the following tools you can use out of the box: 🗺️ ShowPoisOnMap: A tool that can show points of...

Compatible Skills

These tools work well together with openai-function-calling-tools for enhanced workflows:

  • openai-assistant-swarm — semantic(0.36)+complementary+shared_fw(openai)+same_lang+similar_pop+shared_platform (65%)
  • openai-agents-js — semantic(0.18)+complementary+shared_fw(openai)+same_lang+similar_pop+shared_platform (64%)
  • openai-agents-js — semantic(0.25)+complementary+shared_fw(openai)+same_lang+similar_pop+shared_platform (62%)
  • composio — semantic(0.21)+complementary+shared_fw(openai)+same_lang+shared_platform (55%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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