analytical-method-validation

analytical-method-validation is a skill for Claude Code from agentlas-ai/agentlas-desktop. It costs 281 tokens per session (4,376 once invoked), scanned A, a copy of analytical-method-validation, Apache-2.0.

A guide for checking whether laboratory analytical procedures are suitable for their intended use. It covers validation, verification, and transfer under standards such as ICH, USP, CLSI, and ISO/IEC 17025.

In plain words
What is it for?
Use it to plan validation studies for methods such as HPLC, mass spectrometry, PCR, chromatography, and other laboratory assays, then document the results.
Why use it?
It prevents teams from using the wrong standard or choosing success criteria after seeing the results, both of which can cause audit problems.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Good fit Use it to plan validation studies for methods such as HPLC, mass spectrometry, PCR, chromatography, and other laboratory assays, then document the results.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/agentlas-ai/agentlas-desktop/analytical-method-validation
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 analytical-method-validation
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 analytical-method-validation

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/agentlas-ai/agentlas-desktop/analytical-method-validation"><img src="https://agentmods.dev/badge/skills/agentlas-ai/agentlas-desktop/analytical-method-validation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 281 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,376 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 91% 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 $0.00281 $0.04376
Opus 5.5 $0.00112 $0.01750
Sonnet 5.5 $0.00056 $0.00875
Haiku 4.5 $0.00028 $0.00438

Measured 1mo ago against content hash 9f6db7bd7785, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

analytical-method-validation 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 1mo ago.

The scan reads SKILL.md. This mod also ships 8 executable files (scripts/_catalog.py, scripts/_common.py, scripts/check_accuracy_precision.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

91% identical to analytical-method-validation — 76 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/analytical-method-validation/SKILL.md · 317 lines

How it starts

The opening of the file, as written. The whole thing — 317 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Analytical Method Validation

When to use

Any time the question is whether an analytical procedure is fit for its intended purpose: designing a validation study, evaluating validation data, verifying a compendial procedure, transferring a procedure to another laboratory or instrument, or defending any of these in a report.

The two rules

1. Establish which framework governs before designing anything. The same assay validates differently under ICH Q2(R2), USP <1225>, ICH M10, CLSI EP, and ISO/IEC 17025. They differ in which characteristics are required, how the studies are laid out, and whether numeric acceptance criteria are supplied at all. Blending them produces a protocol that satisfies none of them.

2. State acceptance criteria before collecting data. Criteria chosen after seeing results are not acceptance criteria, and deciding them post hoc is a standing audit finding. ICH Q2(R2) deliberately supplies almost no numeric criteria — they have to come from the specification, the analytical target profile (ICH Q14 section 3), or development data. ICH M10 is the exception: it supplies explicit numbers, and they differ between chromatographic assays and ligand binding assays.

Scope

This skill plans studies, computes the statistics correctly, and structures the documentation. It does not decide that a procedure is validated, release a batch, accept or reject a run, close an investigation, or substitute for the analyst, the technical reviewer, the quality unit, or the regulator. Every script reports; none of them concludes.

ICH guidelines are published openly and licensed for reuse with acknowledgement, so their requirements are encoded directly in this skill. USP general chapters, CLSI EP documents, and ISO standards are copyrighted and paywalled. For those, this skill supplies the designation, scope, and where to obtain an authorised copy — never the text, never invented thresholds. Do not ask an agent to retrieve, transcribe, or reconstruct their content. If a number matters and it lives in a paywalled document, read it from the authorised copy.

Read the full file on GitHub · 317 lines

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. 1mo ago First seen · 317 lines · 281 tokens per session scan A 9f6db7bd7785

Subscribe to this mod's changes

analytical-method-validation is a skill published in the GitHub repository agentlas-ai/agentlas-desktop (6 stars, last pushed today), licensed Apache-2.0. It adds 281 tokens to every session and 4,376 once invoked, about $0.0011 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 91% identical to analytical-method-validation, differing in 76 lines, and is treated as a copy.

Related

Other skills, from other repositories

analytical-method-validation

Plans, executes, and documents validation, verification, and transfer of analytical procedures under the governing framework - ICH Q2(R2) and Q14, USP / / , ICH M10 bioanalytical, CLSI EP, or ISO/IEC 17025. Use for HPLC, LC-MS/MS, GC, CE, ICP-MS, dissolution, qNMR, qPCR, NIR, and ligand binding or cell-based assays…

K-Dense-AI/scientific-agent-skills · 281 tokens

auditing-part11-trails

Generates and verifies 21 CFR Part 11-style audit trails — who/what/when, electronic signatures, and tamper-evidence — for OpenMed pipelines in GxP and clinical-trial (GCP) settings. Use when the user runs OpenMed in a regulated/validated environment and needs an attributable, time-stamped, tamper-evident record of…

maziyarpanahi/openmed · 222 tokens

invention-intake

Invention disclosure first-pass screen — novelty, obviousness, §101 eligibility, bar dates, detectability, and strategic value. Use when an invention disclosure comes in and needs triage on whether to pursue a prior-art search and patent counsel review, investigate further, or decline.

anthropics/claude-for-legal · 61 tokens

generating-synthetic-surrogates

Replace detected PHI with realistic, type-matched fake values in OpenMed so clinical notes stay readable and parseable instead of full of [REDACTED] markers. Use when the user wants surrogate names, MRNs, addresses, or dates rather than opaque masks, needs consistent fake identities across a document, must keep notes…

maziyarpanahi/openmed · 145 tokens

fda-database

Query openFDA API for drugs, devices, adverse events, recalls, regulatory submissions (510k, PMA), substance identification (UNII), for FDA regulatory data analysis and safety research.

synthetic-sciences/openscience · 43 tokens

adverse-event-narrative

Generates CIOMS I-compliant ICSR narratives from adverse event case data for FDA and EMA regulatory submission. Includes temporal analysis, MedDRA coding, causality assessment using WHO-UMC or Naranjo criteria, and multi-format output.

aipoch/medical-research-skills · 57 tokens