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 Bilal140202/the-lord-of-the-skills --skill agentcontrol-toolsgit clone --depth 1 https://github.com/Bilal140202/the-lord-of-the-skillsWrote 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/bilal140202/the-lord-of-the-skills/agentcontrol-tools)<a href="https://agentmods.dev/skills/bilal140202/the-lord-of-the-skills/agentcontrol-tools"><img src="https://agentmods.dev/badge/skills/bilal140202/the-lord-of-the-skills/agentcontrol-tools/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/bilal140202/the-lord-of-the-skills/agentcontrol-tools"><img src="https://agentmods.dev/badge/skills/bilal140202/the-lord-of-the-skills/agentcontrol-tools.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 | $0.00033 | $0.02664 |
| Opus 5.5 | $0.00013 | $0.01066 |
| Sonnet 5.5 | $0.00007 | $0.00533 |
| Haiku 4.5 | $0.00003 | $0.00266 |
Grade A, and why
tools 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 — 245 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Config Tools
You're using a skill that will guide you through adding capabilities to your agents through tools (function calling). Your job is to identify what your agent needs to do, create tool definitions, attach them to variations, and verify they work.
Prerequisites
This skill requires the remotely hosted LaunchDarkly MCP server to be configured in your environment.
Required MCP tools:
create-ai-tool-- create a new tool definition with a schemaupdate-ai-config-variation-- attach tools to a config variationget-ai-config-- verify tools are attached to the variation
Optional MCP tools:
list-ai-tools-- browse existing tools in the projectget-ai-tool-- inspect a specific tool's schema
Core Principles
- Start with Capabilities: Think about what your agent needs to do before creating tools
- Framework Matters: LangGraph/CrewAI often auto-generate schemas; OpenAI SDK needs manual schemas
- Create Before Attach: Tools must exist before you can attach them to variations
- Verify: The agent fetches the config to confirm attachment
- Complete the Full Workflow: Listing existing tools is a discovery step, not the end goal. After listing, always proceed to create the requested tool, attach it, and verify. Do not stop after exploration.
Workflow
Step 1: Identify Needed Capabilities
What should the agent be able to do?
- Query databases, call APIs, perform calculations, send notifications
- Check what exists in the codebase (API clients, functions)
- Consider framework: LangGraph/LangChain auto-generate schemas; direct SDK needs manual schemas
If the user asks to check existing tools first, or you have no codebase context about what tools exist, follow this exact order:
list-ai-tools-- explore what existscreate-ai-tool-- create the new tool (with a key different from existing ones)update-ai-config-variation-- attach itget-ai-config-- verify
Call list-ai-tools as your first tool call before any creation. Never stop after listing alone -- always proceed through all four steps.
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 · 245 lines · 33 tokens per session scan A 690c0e55636a
tools is a skill published in the GitHub repository Bilal140202/the-lord-of-the-skills (6 stars, last pushed 1mo ago), licensed MIT. It adds 33 tokens to every session and 2,664 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 2026-09-06.
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