scholar-evaluation

scholar-evaluation is a skill for Claude Code from K-Dense-AI/scientific-agent-skills. It costs 43 tokens per session (2,465 once invoked), scanned A, original, MIT.

A guide to giving traceable, developmental feedback on scholarly work, such as papers, protocols, literature reviews, and research ideas.

In plain words
What is it for?
Use it to review scholarly writing and research processes, map comments to submitted evidence, and audit low-stakes assessment rubrics.
Why use it?
It keeps review focused on improving the work and its evidence instead of ranking people or making high-impact decisions about them.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Good fit Use it to review scholarly writing and research processes, map comments to submitted evidence, and audit low-stakes assessment rubrics.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/k-dense-ai/scientific-agent-skills/scholar-evaluation
About the project

Scientific Agent Skills is a collection of reusable procedures that give AI agents capabilities for scientific research across areas such as biology, chemistry, medicine, and drug discovery. It is used by researchers and by people building AI scientist workflows with compatible coding agents. The catalogue contains many of the project's skills and supporting instructions.

K-Dense-AI/scientific-agent-skills · 44,220 stars · on GitHub · arxiv.org

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 K-Dense-AI/scientific-agent-skills --skill scholar-evaluation
Clone the repo
git clone --depth 1 https://github.com/K-Dense-AI/scientific-agent-skills

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 scholar-evaluation

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/k-dense-ai/scientific-agent-skills/scholar-evaluation"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/scholar-evaluation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 43 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,465 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. Third-party audits
  • Socket pass 12 Apr 2026
  • Snyk warn 12 Apr 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00043 $0.02465
Opus 5 $0.00022 $0.01233
Sonnet 5 $0.00009 $0.00493
Haiku 4.5 $0.00004 $0.00247

Measured 7d ago against content hash 50f2225d1828, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

scholar-evaluation 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 7d ago.

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

Copies of this mod

1 near-identical copy found in the catalogue:

skills/scholar-evaluation/SKILL.md · 314 lines

How it starts

The opening of the file, as written. The whole thing — 314 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Scholar Evaluation

Purpose

Provide developmental, evidence-traceable feedback on a scholarly work: paper, draft, protocol, literature synthesis, or research idea. Use qualitative judgment first. Optional scores only describe how submitted evidence maps to a predeclared bounded rubric.

This skill also audits whether a low-stakes assessment process documents its construct, provenance, rater quality, uncertainty, traceability, sensitivity, fairness, accessibility, privacy, and human governance.

Hard safety boundary

Never use this skill to automate, recommend, materially influence, or score:

  • hiring, promotion, or tenure;
  • admissions;
  • grants or other funding;
  • prizes, honors, or awards;
  • discipline, dismissal, or sanctions; or
  • any other high-impact personnel decision.

Never rank people. Never reduce a person to a composite score. Never infer ability, character, integrity, protected traits, future performance, or worth. A nominal human-in-the-loop does not remove this boundary.

If asked for a prohibited use, stop. Offer developmental comments on a scholarly work or a process-only audit that does not process applications, compare people, recommend an outcome, or advise a decision.

Do not issue publication-readiness, accept/reject, or “top-tier” judgments.

Read references/responsible_assessment.md before any organizational use.

ScholarEval status

The referenced ScholarEval project is an experimental literature-grounded research-idea evaluation framework, not validated psychometrics.

The verified primary record is Moussa et al., ScholarEval: Research Idea Evaluation Grounded in Literature, arXiv:2510.16234v2, revised 2026-02-28. It reports a retrieval-augmented soundness/contribution framework, a 117-idea four-discipline dataset, coverage experiments, and a user study.

Do not generalize those results to person assessment, consequential decisions, all disciplines, or this skill's rubric. No peer-reviewed publication status was verified during the dated review. See references/source_ledger.md.

Read the full file on GitHub · 314 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. 7d ago First seen · 314 lines · 43 tokens per session scan A 50f2225d1828

Subscribe to this mod's changes

scholar-evaluation is a skill published in the GitHub repository K-Dense-AI/scientific-agent-skills (44,220 stars, last pushed 4d ago), licensed MIT. It adds 43 tokens to every session and 2,465 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 2026-09-03.

Related

Other skills, from other repositories

discovery-toolbox

A routed repertoire of 90 scientific thinking operators for biological research agents - visual reasoning, detectability and information budgets, search reframing, causal identification, competing explanations, observation and selection processes, pipeline artifact diagnosis, effort allocation, and confirmation…

dekan-aleksandr/biodiscovery-skills · 122 tokens

discovery-director

Operate as a research director making original discoveries from a given biological question and dataset. Use when the task is open-ended scientific research, exploring omics or experimental data for findings, hypothesis generation and testing, screening a large candidate space of genes, variants, features or…

dekan-aleksandr/biodiscovery-skills · 114 tokens

msh-exam-analysis

A Chinese-language automation tool for the 名师汇出国 education website. It analyzes mock-test mistakes and automates vocabulary listening tests.

JiHuiYiYou/msh-skill · 144 tokens

baoyu-comic

A tool for creating original educational comics that explain knowledge or ideas through multiple illustrated panels. It supports different art styles and tones and can create several comics in one batch.

JimLiu/baoyu-skills · 61 tokens

extract-source-sample

Given the path to a finished content-goose ad-run folder, extract everything that defines that ad — recipe shot list, VO script, characters, voices, world, atom-skills, master mp4 — and emit a source-sample.json in the exact shape the upload-ad-sample skill writes to the Goose Ads library. Also links every character…

gooseworks-ai/goose-skills · 160 tokens

google-search-ads-builder

End-to-end Google Search Ads campaign builder. Performs deep keyword research (competitor SEO, review language mining, Reddit/HN community terminology, site audit), builds keyword architecture with funnel mapping and intent classification, creates ad group structure, generates headline/description variants, builds…

gooseworks-ai/goose-skills · 79 tokens