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 opencue/cuecards --skill agenticx-tool-creatorgit clone --depth 1 https://github.com/opencue/cuecardsWrote 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/opencue/cuecards/agenticx-tool-creator)<a href="https://agentmods.dev/skills/opencue/cuecards/agenticx-tool-creator"><img src="https://agentmods.dev/badge/skills/opencue/cuecards/agenticx-tool-creator/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/opencue/cuecards/agenticx-tool-creator"><img src="https://agentmods.dev/badge/skills/opencue/cuecards/agenticx-tool-creator.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 | $0.00063 | $0.00899 |
| Opus 5.5 | $0.00025 | $0.00360 |
| Sonnet 5.5 | $0.00013 | $0.00180 |
| Haiku 4.5 | $0.00006 | $0.00090 |
Grade A, and why
agenticx-tool-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 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.
This is a copy
100% identical to agenticx-tool-creator — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AgenticX Tool Creator
Guide for building tools that extend agent capabilities.
Tool Architecture
AgenticX tools inherit from BaseTool and are consumed by agents during execution. Three approaches exist:
- Function decorator (
@tool) — fastest for simple tools - Class-based (extend
BaseTool) — for complex or stateful tools - MCP remote tools — for external services via Model Context Protocol
Function Decorator Tools
from agenticx.tools import tool
@tool
def search_web(query: str) -> str:
"""Search the web for information.
Args:
query: The search query string.
Returns:
Search results as text.
"""
# implementation
return f"Results for: {query}"
@tool
def read_file(path: str) -> str:
"""Read contents of a local file."""
with open(path) as f:
return f.read()
The @tool decorator reads the function signature and docstring to generate the tool schema automatically. The docstring is the tool description the LLM sees.
Class-Based Tools
For tools needing initialization, state, or complex logic:
from agenticx.core import BaseTool
class DatabaseQuery(BaseTool):
name = "database_query"
description = "Query the project database."
def __init__(self, connection_string: str):
super().__init__()
self.conn = connect(connection_string)
def _run(self, sql: str) -> str:
return self.conn.execute(sql).fetchall()
Tool Registry
Register and discover tools globally:
from agenticx.core import ToolRegistry
registry = ToolRegistry()
registry.register(search_web)
registry.register(read_file)
# List all registered tools
for t in registry.list_tools():
print(f"{t.name}: {t.description}")
MCP Integration
AgenticX supports the Model Context Protocol for remote tool access.
Connecting to an MCP Server
from agenticx.protocols import MCPClient
client = MCPClient(server_url="http://localhost:3000")
tools = client.list_tools()
# Use MCP tools like local tools
result = client.call_tool("search", {"query": "AI agents"})
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 · 146 lines · 63 tokens per session scan A 4c32c064860d
agenticx-tool-creator is a skill published in the GitHub repository opencue/cuecards (6 stars, last pushed yesterday), licensed MIT. It adds 63 tokens to every session and 899 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to agenticx-tool-creator, differing in 2 lines, and is treated as a copy.
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