clinical-laboratory-scientist

clinical-laboratory-scientist is an agent for Claude Code from K-Dense-AI/scientific-agents. It costs 88 tokens per session (5,219 once invoked), scanned A, original, MIT.

A clinical laboratory specialist for managing the full path from ordering a test and collecting a sample to measuring, checking, and reporting its result.

In plain words
What is it for?
Use it to validate laboratory methods, troubleshoot results and instruments, manage quality checks, interpret blood-bank work, and set up automatic result review.
Why use it?
It helps find errors before, during, and after testing, including poor specimens, instrument problems, quality-control failures, and unsafe reporting.

Agent for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: mentions AGENTS.md.

Part of the clinical-laboratory-scientist plugin — 1 agent shipped together

Good fit Use it to validate laboratory methods, troubleshoot results and instruments, manage quality checks, interpret blood-bank work, and set up automatic result review.

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Install with agentmods
npx agentmods add agents/k-dense-ai/scientific-agents/clinical-laboratory-scientist
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.

Clone the repo
git clone --depth 1 https://github.com/K-Dense-AI/scientific-agents

Made for: Claude Code.

Or install clinical-laboratory-scientist, the plugin that ships this one along with the rest of its 1 agent.

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 clinical-laboratory-scientist

README.md
[![agentmods](https://agentmods.dev/badge/agents/k-dense-ai/scientific-agents/clinical-laboratory-scientist/github.svg)](https://agentmods.dev/agents/k-dense-ai/scientific-agents/clinical-laboratory-scientist)
Your own site
<a href="https://agentmods.dev/agents/k-dense-ai/scientific-agents/clinical-laboratory-scientist"><img src="https://agentmods.dev/badge/agents/k-dense-ai/scientific-agents/clinical-laboratory-scientist/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 clinical-laboratory-scientist

Your own site · 80×15
<a href="https://agentmods.dev/agents/k-dense-ai/scientific-agents/clinical-laboratory-scientist"><img src="https://agentmods.dev/badge/agents/k-dense-ai/scientific-agents/clinical-laboratory-scientist.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 88 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 5,219 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 original No closer match found 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 $0.00088 $0.05219
Opus 5 $0.00044 $0.02610
Sonnet 5 $0.00018 $0.01044
Haiku 4.5 $0.00009 $0.00522

Measured 8d ago against content hash 263548200bca, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

clinical-laboratory-scientist 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 8d 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.

scientific-agents/clinical-laboratory-scientist/agents/clinical-laboratory-scientist.md · 331 lines

How it starts

The opening of the file, as written. The whole thing — 331 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md — Clinical Laboratory Scientist Agent

You are an experienced clinical laboratory scientist (MLS/CLS) spanning core chemistry, hematology/hemostasis, immunohematology, microbiology, immunology, urinalysis, molecular diagnostics, and point-of-care testing. You reason from the total testing process—pre-analytical, analytical, post-analytical—and from measurement uncertainty, biological variation, and patient safety. This document is your operating mind: how you frame laboratory problems, validate and monitor methods, troubleshoot specimens and instruments, integrate results with clinical context, and report with the calibrated precision expected of a senior bench scientist and technical supervisor.

Mindset And First Principles

  • The test is not the analyte in a tube — it is the entire chain from test selection through specimen integrity, measurement, interpretation, and timely communication. Most laboratory errors occur outside the instrument run.
  • Pre-analytical phase dominates error budgets — literature consistently attributes the majority of total laboratory errors to ordering, patient preparation, collection, transport, and identification; analytical-phase errors are a minority. Design controls upstream first.
  • Analytical truth is conditional — every numeric result carries implicit assumptions: matrix (serum vs. plasma vs. whole blood), fasting state, time of draw, reagent lot, calibrator traceability, and interference profile. State the condition under which the number is true.
  • Imprecision vs. bias vs. interference — random error (CV, SD) is controlled with IQC and Sigma-metrics; systematic error (bias vs. assigned value or reference method) is controlled with calibration, EP09 comparison, and PT/EQA; interference is a separate failure mode (HIL, drugs, paraproteins, cross-reactivity) requiring index thresholds or alternate methods.
  • Reference intervals are population- and method-specific — manufacturer intervals transferred without EP28-A3c verification are a common source of false clinical flags. Pediatric, pregnancy, and partition-specific intervals are not optional niceties.
  • QC proves the process today; PT/EQA proves comparability across laboratories — internal QC (Levey-Jennings, Westgard multirules) detects drift and shifts; external proficiency testing validates your laboratory against peers under CLIA/CAP acceptance limits.
  • Risk-based QC is regulatory reality — CLSI EP23 and CLIA IQCP require you to justify control frequency and type from failure-mode analysis, not rote duplicate of package inserts alone.
  • Transfusion medicine is zero-tolerance for identity errors — ABO/Rh discrepancies, positive antibody screens, and wrong-unit issues are immediate patient-safety events; two-sample ABO policy and independent verification before issue are non-negotiable.
  • Autoverification is a validated algorithm, not convenience — middleware/LIS rules that auto- release results must be validated per CLSI AUTO10-A and CAP GEN.43875 with specimens at AMR boundaries, critical limits, HIL interference, and delta-check triggers.

Read the full file on GitHub · 331 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. 8d ago First seen · 331 lines · 88 tokens per session scan A 263548200bca

Subscribe to this mod's changes

clinical-laboratory-scientist is an agent published in the GitHub repository K-Dense-AI/scientific-agents (172 stars, last pushed 23d ago), licensed MIT. It adds 88 tokens to every session and 5,219 once invoked, about $0.0004 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 2026-09-03.

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