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 agentmods add skills/docxology/template/tool-designnpx skills add docxology/template --skill tool-designgit clone --depth 1 https://github.com/docxology/templateWrote 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/docxology/template/tool-design)<a href="https://agentmods.dev/skills/docxology/template/tool-design"><img src="https://agentmods.dev/badge/skills/docxology/template/tool-design.svg" alt="Measured on agentmods" 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 | $0.00109 | $0.03850 |
| Opus 5 | $0.00055 | $0.01925 |
| Sonnet 5 | $0.00022 | $0.00770 |
| Haiku 4.5 | $0.00011 | $0.00385 |
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 — 0 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 — 297 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Tool Design for Agents
Design every tool as a contract between a deterministic system and a non-deterministic agent. Unlike human-facing APIs, agent-facing tools must make the contract unambiguous through the description alone: agents infer intent from descriptions and generate calls that must match expected formats. Every ambiguity becomes a potential failure mode that no amount of prompt engineering can fix.
The unit of work for this skill is a single tool or a tool catalog. Project-shape, pipeline architecture, task-model-fit, and cost-at-the-project-level decisions belong to project-development. Deciding whether to introduce sub-agents belongs to multi-agent-patterns. This skill owns the interface layer that connects deterministic code to the agent.
When to Activate
Activate this skill when the unit of work is a tool:
- Writing a new tool description, schema, or response format.
- Debugging cases where the agent picked the wrong tool or generated malformed calls.
- Consolidating an overlapping tool catalog (the classic "we have 17 tools, the agent picks wrong half the time" case).
- Designing actionable error messages so the agent can self-correct.
- Naming tools and parameters consistently across a catalog (MCP namespacing, verb-noun naming).
- Evaluating a third-party tool against the consolidation principle before adding it.
Do not activate this skill for adjacent work owned by other skills:
- Deciding whether the project should use LLMs at all, or what the pipeline stages should be:
project-development. - Deciding whether to split work across sub-agents or run a single agent with more tools:
multi-agent-patterns. - Reducing the token weight of tool outputs at the trajectory level (observation masking, format-option choice at scale):
context-optimization.
Core Concepts
Design tools around the consolidation principle: if a human engineer cannot definitively say which tool should be used in a given situation, an agent cannot be expected to do better. Reduce the tool set until each tool has one unambiguous purpose, because agents select tools by comparing descriptions and any overlap introduces selection errors.
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 · 297 lines · 109 tokens per session scan A 14f5a12b6911
tool-design is a skill published in the GitHub repository docxology/template (19 stars, last pushed 3d ago), licensed Apache-2.0. It adds 109 tokens to every session and 3,850 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to tool-design, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
browser-trace
Capture a full DevTools-protocol trace of any browser automation — CDP firehose, screenshots, and DOM dumps — then bisect the stream into per-page searchable buckets. Use when the user wants to debug a failed run, audit network/console/DOM activity, attach a trace to an in-progress session, or feed structured per-page…
planning-with-files
Manus-style persistent file-based planning for AI coding agents: keeps taskplan.md, findings.md, and progress.md on disk so work survives context loss and /clear. Use when asked to plan out, break down, or organize a multi-step project, research task, or any work requiring 5+ tool calls. Supports automatic session…
ai-elements
Build AI chat interfaces using ai-elements components — conversations, messages, tool displays, prompt inputs, and more. Use when the user wants to build a chatbot, AI assistant UI, or any AI-powered chat interface.
exa-search
Use Exa MCP for current web, code/docs, company, people, and page-fetch research. Prefer current hosted tool schemas and note deprecated tools.
ontoly-software-graph
Use Ontoly's deterministic Software Graph and MCP capabilities for repository architecture, request tracing, dependency analysis, configuration lookup, and impact analysis before falling back to source search.
kimi-webbridge
Kimi WebBridge lets AI control the user's real browser — navigate, click, type, read, screenshot, and interact with any website using the user's actual login sessions. Use this skill whenever the user wants to interact with websites, automate browser tasks, scrape web content, or perform any action requiring a real…