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 Zaoqu-Liu/ScienceClaw --skill create-tooluniverse-skillgit clone --depth 1 https://github.com/Zaoqu-Liu/ScienceClawWrote 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/zaoqu-liu/scienceclaw/create-tooluniverse-skill)<a href="https://agentmods.dev/skills/zaoqu-liu/scienceclaw/create-tooluniverse-skill"><img src="https://agentmods.dev/badge/skills/zaoqu-liu/scienceclaw/create-tooluniverse-skill/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/zaoqu-liu/scienceclaw/create-tooluniverse-skill"><img src="https://agentmods.dev/badge/skills/zaoqu-liu/scienceclaw/create-tooluniverse-skill.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 | $0.00090 | $0.06691 |
| Opus 5 | $0.00045 | $0.03345 |
| Sonnet 5 | $0.00018 | $0.01338 |
| Haiku 4.5 | $0.00009 | $0.00669 |
Grade A, and why
create-tooluniverse-skill 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 10d 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 — 1,095 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Create ToolUniverse Skill
Systematic workflow for creating production-ready ToolUniverse skills that integrate multiple scientific tools, follow implementation-agnostic standards, and achieve 100% test coverage.
Core Principles (Critical)
CRITICAL - Read devtu-optimize-skills: This skill builds on principles from devtu-optimize-skills. Invoke that skill first or review its 10 pillars:
- TEST FIRST - Never write documentation without testing tools
- Verify tool contracts - Don't trust function names
- Handle SOAP tools - Add
operationparameter where needed - Implementation-agnostic docs - Separate SKILL.md from code
- Foundation first - Use comprehensive aggregators
- Disambiguate carefully - Resolve IDs properly
- Implement fallbacks - Primary → Fallback → Default
- Grade evidence - T1-T4 tiers on claims
- Require quantified completeness - Numeric minimums
- Synthesize - Models and hypotheses, not just lists
When to Use This Skill
Use this skill when:
- Creating new ToolUniverse skills for specific domains
- Building research workflows using scientific tools
- Developing analysis capabilities (e.g., metabolomics, single-cell, cancer genomics)
- Integrating multiple databases into coherent pipelines
- Following up on "create [domain] skill" requests
Overview: 7-Phase Workflow
Phase 1: Domain Analysis →
Phase 2: Tool Discovery & Testing →
Phase 3: Tool Creation (if needed) →
Phase 4: Implementation →
Phase 5: Documentation →
Phase 6: Testing & Validation →
Phase 7: Packaging
Time per skill: ~1.5-2 hours (tested and documented)
Phase 1: Domain Analysis
Objective: Understand the scientific domain and identify required capabilities
Duration: 15 minutes
1.1 Understand Use Cases
Gather concrete examples of how the skill will be used:
- "What analyses should this skill perform?"
- "Can you give examples of typical queries?"
- "What outputs do users expect?"
What ships with it
1 file 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.
- 10d ago First seen · 1,095 lines · 90 tokens per session scan A fa08b73cef29
create-tooluniverse-skill is a skill published in the GitHub repository Zaoqu-Liu/ScienceClaw (60 stars, last pushed 5mo ago), licensed MIT. It adds 90 tokens to every session and 6,691 once invoked, about $0.0005 per session on Opus 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 2026-08-30.
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