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.
npx skills add agentlas-ai/agentlas-desktop --skill scholar-evaluationgit clone --depth 1 https://github.com/agentlas-ai/agentlas-desktopWrote 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/agentlas-ai/agentlas-desktop/scholar-evaluation)<a href="https://agentmods.dev/skills/agentlas-ai/agentlas-desktop/scholar-evaluation"><img src="https://agentmods.dev/badge/skills/agentlas-ai/agentlas-desktop/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/agentlas-ai/agentlas-desktop/scholar-evaluation"><img src="https://agentmods.dev/badge/skills/agentlas-ai/agentlas-desktop/scholar-evaluation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00043 | $0.02465 |
| Opus 5.5 | $0.00017 | $0.00986 |
| Sonnet 5.5 | $0.00009 | $0.00493 |
| Haiku 4.5 | $0.00004 | $0.00247 |
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 1mo 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.
This is a copy
100% 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.
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.
What ships with it
18 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.
- assets/evaluation_template.json 1.3 KB
- assets/evidence_manifest_template.json 1.8 KB
- assets/process_checklist_template.json 2.1 KB
- assets/ratings_template.csv 1.7 KB
- assets/rubric_template.json 12 KB
- references/evaluation_framework.md 9.5 KB
- references/local_tooling.md 7.7 KB
- references/responsible_assessment.md 8.9 KB
- references/security_validation.md 3.8 KB
- references/source_ledger.md 12 KB
- scripts/_common.py 35 KB runs code
- scripts/calculate_scores.py 1.8 KB runs code
- scripts/check_process.py 8.1 KB runs code
- scripts/check_traceability.py 8.9 KB runs code
- scripts/generate_report_scaffold.py 8.8 KB runs code
- scripts/summarize_agreement.py 8.7 KB runs code
- scripts/validate_rubric.py 1.7 KB runs code
- scripts/weight_sensitivity.py 9.0 KB runs code
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.
- 1mo ago First seen · 314 lines · 43 tokens per session scan A 50f2225d1828
scholar-evaluation is a skill published in the GitHub repository agentlas-ai/agentlas-desktop (6 stars, last pushed today), licensed Apache-2.0. 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 100% identical to scholar-evaluation, differing in 19 lines, and is treated as a copy.
Other skills, from other repositories
tbtools
Use when the user asks about TBtools, TBtools-II, TBtools RPC API, TBtools CLI, or bioinformatics operations available through TBtools such as sequence manipulation, BLAST, GFF/GTF/GXF processing, expression tables, heatmaps, trees, MCScanX, DIAMOND, HMMER, MUSCLE, and IQ-TREE.
electron-expert
Expert in Electron framework, desktop app development, IPC, and cross-platform packaging. Use when the user mentions desktop, Node.js, cross platform, Windows, macOS, or Linux, or when the task involves Electron Architecture, Process Types, IPC Communication, or App Lifecycle.
research-orchestrator
Becomes a principal research scientist who orchestrates deep, multi-source research by coordinating evidence gathering, grading source quality, and synthesizing findings with explicit confidence levels. Use when the user needs a comprehensive research report on a complex topic, evidence-based analysis with source…
autoresearch
Run an auto research / autoresearch loop for measurable improvements. Use when optimizing a skill, agent, prompt, code path, benchmark, or other target with a mechanical metric: baseline, mutate one thing, verify, keep or discard, log, chart progress, and optionally save improved custom skills or agents through Open…
architecture-diagram
How to draw and maintain the architecture diagram Ensemblr keeps for a workspace — ensemblrgetarchitecturediagram to fetch the stored one (it answers with null when nobody has drawn this workspace yet), the IR shape, how to derive it from the codebase, and ensemblrupdatearchitecturediagram to store it. Read this when…
scaffold-lean-library
Scaffold a Lean 4 library with Mathlib or PFR, Lake tests, and CI. Use for "new Lean project"; to edit Lean, use write-lean-code.