assess-model-evaluation-diagnostics

assess-model-evaluation-diagnostics is a skill for Claude Code from malekokour/clinpharm-pmx-skills. It costs 118 tokens per session (2,330 once invoked), scanned A, original, MIT.

A sourced review of evidence used to evaluate and diagnose pharmacokinetic or other quantitative drug models. Model diagnostics are checks of how well a model represents the available data and where it may fail.

In plain words
What is it for?
Use it to assess model-evaluation and diagnostic materials, verify supporting evidence, and flag issues for qualified pharmacometrics practitioners.
Why use it?
It gathers findings, missing items, and contradictions in one traceable register without deciding whether the model is acceptable for clinical or regulatory use.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Part of the clinpharm-pmx-skills plugin — 145 skills shipped together

Good fit Use it to assess model-evaluation and diagnostic materials, verify supporting evidence, and flag issues for qualified pharmacometrics practitioners.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/malekokour/clinpharm-pmx-skills/assess-model-evaluation-diagnostics
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 malekokour/clinpharm-pmx-skills --skill assess-model-evaluation-diagnostics
Clone the repo
git clone --depth 1 https://github.com/malekokour/clinpharm-pmx-skills

Made for: Claude Code.

Or install clinpharm-pmx-skills, the plugin that ships this one along with the rest of its 145 skills.

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 assess-model-evaluation-diagnostics

README.md
[![agentmods](https://agentmods.dev/badge/skills/malekokour/clinpharm-pmx-skills/assess-model-evaluation-diagnostics/github.svg)](https://agentmods.dev/skills/malekokour/clinpharm-pmx-skills/assess-model-evaluation-diagnostics)
Your own site
<a href="https://agentmods.dev/skills/malekokour/clinpharm-pmx-skills/assess-model-evaluation-diagnostics"><img src="https://agentmods.dev/badge/skills/malekokour/clinpharm-pmx-skills/assess-model-evaluation-diagnostics/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 assess-model-evaluation-diagnostics

Your own site · 80×15
<a href="https://agentmods.dev/skills/malekokour/clinpharm-pmx-skills/assess-model-evaluation-diagnostics"><img src="https://agentmods.dev/badge/skills/malekokour/clinpharm-pmx-skills/assess-model-evaluation-diagnostics.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 118 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,330 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 $0.00118 $0.02330
Opus 5 $0.00059 $0.01165
Sonnet 5 $0.00024 $0.00466
Haiku 4.5 $0.00012 $0.00233

Measured 11d ago against content hash 4b7e421129fd, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

assess-model-evaluation-diagnostics 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 11d 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.

skills/assess-model-evaluation-diagnostics/SKILL.md · 224 lines

How it starts

The opening of the file, as written. The whole thing — 224 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Assess Model Evaluation Diagnostics

Model evaluation and diagnostics evidence pack — bounded review / prepare / structure workflow for the L3 task Model evaluation and diagnostics (Band A · Quantitative pharmacology).

Skills review, reconcile, verify, structure and flag. Qualified humans decide, approve, sign off, submit and act.

Four-box contract

Box Content
Trigger Please assess the materials for Model evaluation and diagnostics and produce a sourced finding register — do not decide the clinical or regulatory outcome.
Input Primary package for Model evaluation and diagnostics plus the supporting pack in Required inputs
Output Source-linked finding register with denominators; gap / contradiction flags; refuse list
Refuses Decide the outcome of Model evaluation and diagnostics; approve or submit related documents; select or adjust a dose; speak for the sponsor to an agency

Who this is for

Clinical pharmacology or pharmacometrics practitioners working on Quantitative pharmacology who need a repeatable, sourced pass over Model evaluation and diagnostics — not a decision and not a filing.

When to use this skill

  • "Please assess the materials for Model evaluation and diagnostics and produce a sourced finding register — do not decide the clinical or regulatory outcome."
  • "What is evidenced, missing, or inconsistent for: Model evaluation and diagnostics?"
  • "Trace every material statement about Model evaluation and diagnostics to a locator."
  • "Prepare the review pack for Model evaluation and diagnostics before a meeting or QC cut."

When NOT to use this skill

Request Why not this skill Where it belongs
Decide clinical significance, dose, or labelling outcome Human decision Qualified clinical pharmacologist / labelling owner
Approve, sign off, or submit Human authority Accountable owner / signatory
A different L3 neighbour sharing vocabulary only Wrong grain or human-owned the neighbour skill named by the router
Decide clinical significance or dose Wrong grain or human-owned qualified clinical pharmacologist
Run or re-fit a model as the primary ask Modelling execution Modelling environment + human modeller

Read the full file on GitHub · 224 lines

Files

What ships with it

2 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. 11d ago First seen · 224 lines · 118 tokens per session scan A 4b7e421129fd

Subscribe to this mod's changes

assess-model-evaluation-diagnostics is a skill published in the GitHub repository malekokour/clinpharm-pmx-skills (6 stars, last pushed 10d ago), licensed MIT. It adds 118 tokens to every session and 2,330 once invoked, about $0.0006 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 2026-08-31.

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