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/legendtkl/agentic-skill-router/skill-035npx skills add legendtkl/agentic-skill-router --skill skill-035git clone --depth 1 https://github.com/legendtkl/agentic-skill-routerWrote 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/legendtkl/agentic-skill-router/skill-035)<a href="https://agentmods.dev/skills/legendtkl/agentic-skill-router/skill-035"><img src="https://agentmods.dev/badge/skills/legendtkl/agentic-skill-router/skill-035.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 5.1 | $0.00018 | $0.00928 |
| Opus 5 | $0.00009 | $0.00464 |
| Sonnet 5 | $0.00004 | $0.00186 |
| Haiku 4.5 | $0.00002 | $0.00093 |
Grade A, and why
skill-035 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 6d 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
92% identical to pint-compute — 6 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 — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Unit Computation with Pint
Cognitive prosthetics for unit-aware computation. Use Pint for converting between units, performing unit arithmetic, checking dimensional compatibility, and simplifying compound units.
When to Use
- Converting between units (meters to feet, kg to pounds)
- Unit-aware arithmetic (velocity x time = distance)
- Dimensional analysis (is force = mass x acceleration?)
- Simplifying compound units to base or named units
- Parsing and analyzing quantities with units
Quick Reference
| I want to... | Command | Example |
|---|---|---|
| Convert units | convert |
convert "5 meters" --to feet |
| Unit math | calc |
calc "10 m/s * 5 s" |
| Check dimensions | check |
check newton --against "kg * m / s^2" |
| Parse quantity | parse |
parse "100 km/h" |
| Simplify units | simplify |
simplify "1 kg*m/s^2" |
Commands
parse
Parse a quantity string into magnitude, units, and dimensionality.
uv run python -m runtime.harness scripts/pint_compute.py \
parse "100 km/h"
uv run python -m runtime.harness scripts/pint_compute.py \
parse "9.8 m/s^2"
convert
Convert a quantity to different units.
uv run python -m runtime.harness scripts/pint_compute.py \
convert "5 meters" --to feet
uv run python -m runtime.harness scripts/pint_compute.py \
convert "100 km/h" --to mph
uv run python -m runtime.harness scripts/pint_compute.py \
convert "1 atmosphere" --to pascal
calc
Perform unit-aware arithmetic. Operators must be space-separated.
uv run python -m runtime.harness scripts/pint_compute.py \
calc "5 m * 3 s"
uv run python -m runtime.harness scripts/pint_compute.py \
calc "10 m / 2 s"
uv run python -m runtime.harness scripts/pint_compute.py \
calc "5 meters + 300 cm"
check
Check if two units have compatible dimensions.
uv run python -m runtime.harness scripts/pint_compute.py \
check newton --against "kg * m / s^2"
uv run python -m runtime.harness scripts/pint_compute.py \
check joule --against "kg * m^2 / s^2"
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.
- 6d ago First seen · 127 lines · 18 tokens per session scan A 7d3045556da8
skill-035 is a skill published in the GitHub repository legendtkl/agentic-skill-router (5 stars, last pushed 3mo ago), licensed MIT. It adds 18 tokens to every session and 928 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to pint-compute, differing in 6 lines, and is treated as a copy.
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