claude-scientific-writer: Skill for Claude Code

.claude/skills/scholar-evaluation/SKILL.md

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

A guide to giving developmental, evidence-traceable feedback on papers, drafts, research plans, literature reviews, and research ideas. It can also audit low-stakes research-assessment rubrics.

In plain words
What is it for?
Use it to review research work or audit a low-stakes assessment process; it is not for ranking people or making decisions about hiring, admissions, funding, promotion, or discipline.
Why use it?
It helps make scholarly feedback more grounded in submitted evidence and exposes weaknesses in how a review or assessment process handles quality, uncertainty, fairness, and traceability.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

This is K-Dense-AI/claude-scientific-writer's own configuration. It tells Claude Code how to work on claude-scientific-writer itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything claude-scientific-writer configures →

About the project

Claude Scientific Writer is an AI-assisted research and writing tool that searches literature and produces documents such as scientific papers, reports, posters, grant proposals, and reviews with citations. Researchers and technical writers can use it as a Claude Code plugin, Python package, or command-line tool, with the catalogue entries defining agent workflows for it.

K-Dense-AI/claude-scientific-writer · 2,530 stars · on GitHub · k-dense.ai

Reuse

Borrowing it

Nothing to install: this file belongs to K-Dense-AI/claude-scientific-writer. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/K-Dense-AI/claude-scientific-writer/main/.claude/skills/scholar-evaluation/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/K-Dense-AI/claude-scientific-writer

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/claude-scientific-writer/scholar-evaluation/github.svg)](https://agentmods.dev/skills/k-dense-ai/claude-scientific-writer/scholar-evaluation)
Your own site
<a href="https://agentmods.dev/skills/k-dense-ai/claude-scientific-writer/scholar-evaluation"><img src="https://agentmods.dev/badge/skills/k-dense-ai/claude-scientific-writer/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/claude-scientific-writer/scholar-evaluation"><img src="https://agentmods.dev/badge/skills/k-dense-ai/claude-scientific-writer/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.
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 $0.00043 $0.02465
Opus 5.5 $0.00017 $0.00986
Sonnet 5.5 $0.00009 $0.00493
Haiku 4.5 $0.00004 $0.00247

Measured 28d ago against content hash 50f2225d1828, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, 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 28d 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

This is a copy

91% identical to scholar-evaluation — 19 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.

.claude/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. 28d ago Changed · +17 lines 50f2225d1828
  2. 1mo ago First seen · 297 lines · 43 tokens per session scan A 902c41a08cb5

Subscribe to this mod's changes

scholar-evaluation is a skill published in the GitHub repository K-Dense-AI/claude-scientific-writer (2,530 stars, last pushed 7d ago), licensed MIT. It adds 43 tokens to every session and 2,465 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 91% identical to scholar-evaluation, differing in 19 lines, and is treated as a copy.

Related

Other skills, from other repositories

agents-v2-py

Build container-based Foundry Agents with Azure AI Projects SDK (ImageBasedHostedAgentDefinition). Use when creating hosted agents with custom container images in Azure AI Foundry.

lingxling/awesome-skills-cn · 39 tokens

analytics-product

Analytics de produto — PostHog, Mixpanel, eventos, funnels, cohorts, retencao, north star metric, OKRs e dashboards de produto.

lingxling/awesome-skills-cn · 35 tokens

api-security-best-practices

Implement secure API design patterns including authentication, authorization, input validation, rate limiting, and protection against common API vulnerabilities.

lingxling/awesome-skills-cn · 29 tokens

antigravity-workflows

Use when asked to ship a SaaS MVP, audit application security, build an AI agent, run browser QA, or design a domain model with multiple skills and verified checkpoints.

lingxling/awesome-skills-cn · 41 tokens

frontmcp-development

Use when building any FrontMCP server component other than a tool (for tools, use create-tool). Covers @Resource static resources and parameterized URI templates; @Prompt reusable prompts (RAG, multi-turn); @Provider singleton dependency-injection providers (database pools, API clients); @Agent autonomous LLM agents…

agentfront/frontmcp · 196 tokens

loop-designer

Compile a goal into a durable, file-backed agent loop — a .loop/ / charter any coding agent (Claude Code, Codex, Gemini, Grok) can execute unattended. Use when the user wants to "build a loop", "design a loop", "run X continuously/24-7", "make an agent keep working on Y", automate recurring work, or convert a big…

frankxai/claude-skills-library · 106 tokens