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 agentailor/create-mcp-server --skill tool-designgit clone --depth 1 https://github.com/agentailor/create-mcp-serverWrote 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/agentailor/create-mcp-server/tool-design)<a href="https://agentmods.dev/skills/agentailor/create-mcp-server/tool-design"><img src="https://agentmods.dev/badge/skills/agentailor/create-mcp-server/tool-design/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/agentailor/create-mcp-server/tool-design"><img src="https://agentmods.dev/badge/skills/agentailor/create-mcp-server/tool-design.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 | $0.00135 | $0.02746 |
| Opus 5.5 | $0.00054 | $0.01098 |
| Sonnet 5 | $0.00027 | $0.00549 |
| Haiku 4.5 | $0.00014 | $0.00275 |
Grade A, and why
tool-design 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 3d 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 tool-design — 214 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 — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Tool Design
Overview
A tool is a contract between a deterministic system and a non-deterministic caller. A normal API assumes a rational developer who reads the docs, handles error codes, and knows which endpoint to call. An agent breaks all of those assumptions: it may pick the wrong tool because two names look alike, pass malformed parameters despite a clear schema, pull back a dataset that blows its own context window, or misread a cryptic error and retry the same failing call.
So tools for agents are designed defensively: clear enough that the agent can't easily misuse them, informative enough to steer the agent toward a better next move, and lean enough to spend the context window carefully.
The payoff: agent and human ergonomics align. A tool that an agent uses well is almost always a tool a human finds intuitive too. Designing for a non-deterministic caller just produces a better API.
None of this is framework- or language-specific. The same five principles apply whether the tool is an MCP server tool, a LangChain/LangGraph tool, an OpenAI/Anthropic function-calling definition, or a plain function exposed to a model — and whether it's written in TypeScript, Python, or anything else. What varies is the syntax of name / description / parameters / returns; the design thinking does not. See references/examples.md for the same tool proven across languages and surfaces.
The Five Principles
Apply these when writing or reviewing any tool. The deep dive with worked schema shapes is in references/principles.md.
1. Strategic selection
Build tools around user workflows, not database schemas or API endpoints. Don't wrap every endpoint as its own tool — the agent then struggles to choose among near-duplicates and you spend prompt budget documenting all of them. Consolidate related operations into one well-parameterized tool when it maps to how a user thinks about the task.
What ships with it
3 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.
- 3d ago First seen · 108 lines · 135 tokens per session scan A 62bb946ae5a1
tool-design is a skill published in the GitHub repository agentailor/create-mcp-server (14 stars, last pushed 4d ago), licensed Apache-2.0. It adds 135 tokens to every session and 2,746 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to tool-design, differing in 214 lines, and is treated as a copy.
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