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 Ghosteken/agent-harness --skill agent-tool-buildergit clone --depth 1 https://github.com/Ghosteken/agent-harnessWrote 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/ghosteken/agent-harness/agent-tool-builder)<a href="https://agentmods.dev/skills/ghosteken/agent-harness/agent-tool-builder"><img src="https://agentmods.dev/badge/skills/ghosteken/agent-harness/agent-tool-builder/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/ghosteken/agent-harness/agent-tool-builder"><img src="https://agentmods.dev/badge/skills/ghosteken/agent-harness/agent-tool-builder.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 | $0.00057 | $0.04507 |
| Opus 5.5 | $0.00023 | $0.01803 |
| Sonnet 5.5 | $0.00011 | $0.00901 |
| Haiku 4.5 | $0.00006 | $0.00451 |
Grade A, and why
agent-tool-builder scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
data = weather_api.fetch(location) This is a copy
98% identical to agent-tool-builder — 650 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 — 715 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Tool Builder
Tools are how AI agents interact with the world. A well-designed tool is the difference between an agent that works and one that hallucinates, fails silently, or costs 10x more tokens than necessary.
This skill covers tool design from schema to error handling. JSON Schema best practices, description writing that actually helps the LLM, validation, and the emerging MCP standard that's becoming the lingua franca for AI tools.
Key insight: Tool descriptions are more important than tool implementations. The LLM never sees your code - it only sees the schema and description.
Principles
- Description quality > implementation quality for LLM accuracy
- Aim for fewer than 20 tools - more causes confusion
- Every tool needs explicit error handling - silent failures poison agents
- Return strings, not objects - LLMs process text
- Validation gates before execution - reject, fix, or escalate, never silent fail
- Test tools with the LLM, not just unit tests
Capabilities
- agent-tools
- function-calling
- tool-schema-design
- mcp-tools
- tool-validation
- tool-error-handling
Scope
- multi-agent-coordination → multi-agent-orchestration
- agent-memory → agent-memory-systems
- api-design → api-designer
- llm-prompting → prompt-engineering
Tooling
Standards
- JSON Schema - When: All tool definitions Note: The universal format for tool schemas
- MCP (Model Context Protocol) - When: Building reusable, cross-platform tools Note: Anthropic's open standard, widely adopted
Frameworks
- Anthropic SDK - When: Claude-based agents Note: Beta tool runner handles most complexity
- OpenAI Functions - When: OpenAI-based agents Note: Use strict mode for guaranteed schema compliance
- Vercel AI SDK - When: Multi-provider tool handling Note: Abstracts differences between providers
- LangChain Tools - When: LangChain-based agents Note: Converts MCP tools to LangChain format
Patterns
Tool Schema Design
Creating clear, unambiguous JSON Schema for tools
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 · 715 lines · 57 tokens per session scan A d32f031ee373
agent-tool-builder is a skill published in the GitHub repository Ghosteken/agent-harness (4 stars, last pushed today), licensed MIT. It adds 57 tokens to every session and 4,507 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). It is 98% identical to agent-tool-builder, differing in 650 lines, and is treated as a copy.
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