relsa-severity-assessment

relsa-severity-assessment is a skill for Claude Code from agentlas-ai/agentlas-desktop. It costs 182 tokens per session (5,021 once invoked), scanned A, a copy of relsa-severity-assessment, Apache-2.0.

A method for combining several laboratory-animal welfare measurements into one severity score and forecasting how that score may change. It supports humane endpoint decisions, which are decisions about when to stop a study to prevent unnecessary suffering.

In plain words
What is it for?
It is for analysing repeated welfare measurements, calculating RELSA severity scores, forecasting future scores with ARIMA time-series models, and identifying possible attention or danger zones.
Why use it?
Looking at weight, temperature, activity, and clinical signs separately can hide the animal’s overall condition. Combining them and forecasting the trend can help identify animals needing attention sooner.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Good fit It is for analysing repeated welfare measurements, calculating RELSA severity scores, forecasting future scores with ARIMA time-series models, and identifying possible attention or danger zones.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/agentlas-ai/agentlas-desktop/relsa-severity-assessment
Install

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.

Any agent
npx skills add agentlas-ai/agentlas-desktop --skill relsa-severity-assessment
Clone the repo
git clone --depth 1 https://github.com/agentlas-ai/agentlas-desktop

Made for: Claude Code.

Wrote 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.

agentmods badge for relsa-severity-assessment

README.md
[![agentmods](https://agentmods.dev/badge/skills/agentlas-ai/agentlas-desktop/relsa-severity-assessment/github.svg)](https://agentmods.dev/skills/agentlas-ai/agentlas-desktop/relsa-severity-assessment)
Your own site
<a href="https://agentmods.dev/skills/agentlas-ai/agentlas-desktop/relsa-severity-assessment"><img src="https://agentmods.dev/badge/skills/agentlas-ai/agentlas-desktop/relsa-severity-assessment/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.

agentmods 80×15 button for relsa-severity-assessment

Your own site · 80×15
<a href="https://agentmods.dev/skills/agentlas-ai/agentlas-desktop/relsa-severity-assessment"><img src="https://agentmods.dev/badge/skills/agentlas-ai/agentlas-desktop/relsa-severity-assessment.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 182 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 5,021 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00182 $0.05021
Opus 5.5 $0.00073 $0.02008
Sonnet 5.5 $0.00036 $0.01004
Haiku 4.5 $0.00018 $0.00502

Measured 19d ago against content hash 08c2abddda92, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

relsa-severity-assessment 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 19d ago.

The scan reads SKILL.md. This mod also ships 4 executable files (scripts/_common.py, scripts/forecast_relsa.py, scripts/kde_thresholds.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Origin

This is a copy

100% identical to relsa-severity-assessment — 191 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.

plugins/agentlas-science-skills/skills/relsa-severity-assessment/SKILL.md · 372 lines

How it starts

The opening of the file, as written. The whole thing — 372 lines — stays where its author put it; the contents beside it link to each section on GitHub.

RELSA severity assessment and humane endpoint forecasting

Overview

Severity assessment in animal research is legally mandatory and scientifically load-bearing: it drives humane endpoint decisions, and poor welfare monitoring degrades reproducibility. The usual practice evaluates each readout in isolation — weight loss here, a clinical score there — which makes it hard to say how badly an individual animal is actually doing.

This skill implements two published procedures that address that:

  • RELSA (Talbot et al., 2022) combines several outcome measures into one score per animal per time point, expressed relative to a reference set of known burden. RELSA = 0 is baseline; RELSA = 1 means the animal has reached the reference set's maximum deviation.
  • foRcast (Lutscher et al., 2026) fits an ARIMA model to an individual animal's RELSA trajectory and forecasts the next score with a 95% prediction interval, so animals heading for a humane endpoint can be identified before they get there. Kernel density estimation on the RELSA scale supplies candidate attention and danger zones for interpretation.

The point is refinement: give at-risk animals attention earlier, and avoid euthanising animals that would have recovered. Both procedures are aids to severity assessment, not decision rules — see Boundaries.

When to use this skill

  • Combining weight loss, temperature, clinical scoring, biomarkers, or telemetry into a single per-animal severity score
  • Asking which animals in a cohort are at risk of reaching a humane endpoint, or predicting the severity score at a coming time point
  • Comparing severity between treatment groups, interventions, or animal models on a common relative scale
  • Defining thresholds or zones on a severity scale from the data
  • Writing the severity-assessment section of an animal welfare report, a 3Rs/refinement analysis, or an application under EU Directive 2010/63/EU

Read the full file on GitHub · 372 lines

Files

What ships with it

7 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.

Changes

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.

  1. 21d ago Changed · -44 lines 0580bbba8e54
  2. 1mo ago First seen · 372 lines · 182 tokens per session scan A 08c2abddda92

Subscribe to this mod's changes

relsa-severity-assessment is a skill published in the GitHub repository agentlas-ai/agentlas-desktop (6 stars, last pushed yesterday), licensed Apache-2.0. It adds 182 tokens to every session and 5,021 once invoked, about $0.0007 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to relsa-severity-assessment, differing in 191 lines, and is treated as a copy.

Related

Other skills, from other repositories

tbtools

Use when the user asks about TBtools, TBtools-II, TBtools RPC API, TBtools CLI, or bioinformatics operations available through TBtools such as sequence manipulation, BLAST, GFF/GTF/GXF processing, expression tables, heatmaps, trees, MCScanX, DIAMOND, HMMER, MUSCLE, and IQ-TREE.

xuzhougeng/wispterm · 77 tokens

electron-expert

Expert in Electron framework, desktop app development, IPC, and cross-platform packaging. Use when the user mentions desktop, Node.js, cross platform, Windows, macOS, or Linux, or when the task involves Electron Architecture, Process Types, IPC Communication, or App Lifecycle.

personamanagmentlayer/pcl · 59 tokens

research-orchestrator

Becomes a principal research scientist who orchestrates deep, multi-source research by coordinating evidence gathering, grading source quality, and synthesizing findings with explicit confidence levels. Use when the user needs a comprehensive research report on a complex topic, evidence-based analysis with source…

FerroxLabs/wayland · 109 tokens

autoresearch

Run an auto research / autoresearch loop for measurable improvements. Use when optimizing a skill, agent, prompt, code path, benchmark, or other target with a mechanical metric: baseline, mutate one thing, verify, keep or discard, log, chart progress, and optionally save improved custom skills or agents through Open…

joe-broadhead/open-cowork · 0 tokens

architecture-diagram

How to draw and maintain the architecture diagram Ensemblr keeps for a workspace — ensemblrgetarchitecturediagram to fetch the stored one (it answers with null when nobody has drawn this workspace yet), the IR shape, how to derive it from the codebase, and ensemblrupdatearchitecturediagram to store it. Read this when…

ensemblr-hq/ensemblr · 94 tokens

scaffold-lean-library

Scaffold a Lean 4 library with Mathlib or PFR, Lake tests, and CI. Use for "new Lean project"; to edit Lean, use write-lean-code.

cboone/agent-harness-plugins · 43 tokens