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 agentjido/jido_ai --skill unit-convertergit clone --depth 1 https://github.com/agentjido/jido_aiWrote 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/agentjido/jido_ai/unit-converter)<a href="https://agentmods.dev/skills/agentjido/jido_ai/unit-converter"><img src="https://agentmods.dev/badge/skills/agentjido/jido_ai/unit-converter/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/agentjido/jido_ai/unit-converter"><img src="https://agentmods.dev/badge/skills/agentjido/jido_ai/unit-converter.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00019 | $0.00423 |
| Opus 5 | $0.00010 | $0.00211 |
| Sonnet 5 | $0.00004 | $0.00085 |
| Haiku 4.5 | $0.00002 | $0.00042 |
Grade A, and why
unit-converter 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 4d 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.
What it actually says
Unit Converter Skill
Purpose
Use this skill when users ask about unit conversions for temperature, distance, or weight.
Available Operations
Temperature
convert_temperature(value, from, to)- Convert between Celsius, Fahrenheit, and Kelvin- Common conversions: C↔F, C↔K, F↔K
Distance
convert_distance(value, from, to)- Convert between metric and imperial- Supports: meters, kilometers, miles, feet, inches, yards
Weight
convert_weight(value, from, to)- Convert between weight units- Supports: kilograms, pounds, ounces, grams, stones
Workflow
- Identify the conversion type (temperature, distance, or weight)
- Extract the value and units from the user's request
- Call the appropriate conversion tool with correct parameters
- Present the result with both original and converted values
Examples
User: "What is 100°F in Celsius?" → convert_temperature(100, "fahrenheit", "celsius") → "100°F = 37.78°C"
User: "How many kilometers is a marathon?"
→ convert_distance(26.2, "miles", "kilometers")
→ "A marathon (26.2 miles) = 42.16 km"
User: "Convert 150 pounds to kilograms" → convert_weight(150, "pounds", "kilograms") → "150 lbs = 68.04 kg"
Best Practices
- Always show both the original and converted values
- Round to 2 decimal places for readability
- Include the unit abbreviations for clarity
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.
- 4d ago Changed · -3 lines 11b02fd5b7cd
- 9d ago First seen · 59 lines · 19 tokens per session scan A 1f2b0cf947f7
unit-converter is a skill published in the GitHub repository agentjido/jido_ai (203 stars, last pushed today), licensed Apache-2.0. It adds 19 tokens to every session and 423 once invoked, about $0.0001 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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