Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/pantheon-org/tekhnenpx agentmods add skills/pantheon-org/tekhne/scholar-evaluationWrote 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.
[](https://agentmods.dev/skills/pantheon-org/tekhne/scholar-evaluation)<a href="https://agentmods.dev/skills/pantheon-org/tekhne/scholar-evaluation"><img src="https://agentmods.dev/badge/skills/pantheon-org/tekhne/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.
<a href="https://agentmods.dev/skills/pantheon-org/tekhne/scholar-evaluation"><img src="https://agentmods.dev/badge/skills/pantheon-org/tekhne/scholar-evaluation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00073 | $0.02853 |
| Opus 5 | $0.00036 | $0.01426 |
| Sonnet 5 | $0.00015 | $0.00571 |
| Haiku 4.5 | $0.00007 | $0.00285 |
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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 355 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Scholar Evaluation
Overview
Apply the ScholarEval framework to systematically evaluate scholarly and research work. This skill provides structured evaluation methodology based on peer-reviewed research assessment criteria, enabling comprehensive analysis of academic papers, research proposals, literature reviews, and scholarly writing across multiple quality dimensions.
Mindset
Evaluation is a service to the author, not a verdict. Three principles govern every assessment:
- Evidence first — every strength and weakness claim must cite a specific section, figure, or sentence from the work. Generic statements ("the methodology is weak") without evidence are useless.
- Stage-appropriate expectations — a first draft is not a submission-ready manuscript. ALWAYS adjust thresholds to the work's stated stage and purpose before scoring.
- Constructive framing — identify what needs improving and why it matters, not just what is wrong. The evaluation is complete only when the author knows what to do next.
# Load the evaluation framework before scoring any dimension
# See references/evaluation_framework.md for detailed rubrics
When to Use This Skill
Use this skill when:
- Evaluating research papers for quality and rigor
- Assessing literature review comprehensiveness and quality
- Reviewing research methodology design
- Scoring data analysis approaches
- Evaluating scholarly writing and presentation
- Providing structured feedback on academic work
- Benchmarking research quality against established criteria
- Assessing publication readiness for target venues
- Providing quantitative evaluation to complement qualitative peer review
When Not to Use
- The goal is factual verification (claim checking), not quality assessment — use a fact-check or reproducibility workflow instead
- The work requires domain-specific technical review beyond the ScholarEval dimensions (e.g., clinical safety review, legal analysis)
- The author has requested a positive endorsement rather than an honest evaluation — do not produce a biased report
What ships with it
9 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.
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.
- 9d ago First seen · 355 lines · 73 tokens per session scan A 4ca76cce62cc
scholar-evaluation is a skill published in the GitHub repository pantheon-org/tekhne (10 stars, last pushed yesterday), licensed MIT. It adds 73 tokens to every session and 2,853 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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