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 OpenLAIR/OpenSkill --skill evo-r2r-linearizationgit clone --depth 1 https://github.com/OpenLAIR/OpenSkillWrote 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/openlair/openskill/evo-r2r-linearization)<a href="https://agentmods.dev/skills/openlair/openskill/evo-r2r-linearization"><img src="https://agentmods.dev/badge/skills/openlair/openskill/evo-r2r-linearization/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/openlair/openskill/evo-r2r-linearization"><img src="https://agentmods.dev/badge/skills/openlair/openskill/evo-r2r-linearization.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 | $0.00045 | $0.00324 |
| Opus 5 | $0.00023 | $0.00162 |
| Sonnet 5 | $0.00009 | $0.00065 |
| Haiku 4.5 | $0.00005 | $0.00032 |
Grade A, and why
evo-r2r-linearization 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 yesterday.
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
evo-r2r-linearization
Computes linearized state-space model for R2R web handling systems.
Usage
import sys
sys.path.insert(0, '/app/environment/skills/evo-r2r-linearization/scripts')
from utils import (
compute_steady_state_velocities,
compute_steady_state_torques,
build_continuous_AB,
discretize_system,
compute_lqr_gain,
get_full_reference_state
)
Key Functions
compute_steady_state_velocities(T_ref, EA, v0)- Cascade velocities using (EA-T) formulacompute_steady_state_torques(T_ref, v_ref, R, fb)- Compute equilibrium torquesbuild_continuous_AB(T_ss, v_ss, EA, L, R, J, fb, v0)- Build 12x12 A and 12x6 B Jacobiansdiscretize_system(A_cont, B_cont, dt)- ZOH discretization via scipycompute_lqr_gain(Ad, Bd, Q, R_mat)- Solve DARE, return K_lqr and Pget_full_reference_state(T_ref, EA, v0, R, fb)- Get full x_ref and u_ref
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.
- yesterday First seen · 31 lines · 45 tokens per session scan A 0e4d483ed986
evo-r2r-linearization is a skill published in the GitHub repository OpenLAIR/OpenSkill (90 stars, last pushed 2d ago), licensed Apache-2.0. It adds 45 tokens to every session and 324 once invoked, about $0.0002 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 2026-09-11.
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