Academic Paper Strategist
AAASS554/codex-academic-paper-skills
A skill your agent uses when the user needs to plan, de-risk, or ground a software engineering / computer science undergraduate thesis from a real codebase before final writing.
Critically assess and improve a legal scholarly thesis, article idea, student note, seminar-paper claim, or research agenda using Eugene Volokh's novelty, nonobviousness, utility, and soundness…
$ npx skills add lawve-ai/awesome-legal-skills --skill thesis-assesor -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install lawve-ai/awesome-legal-skills thesis-assesor --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/lawve-ai/awesome-legal-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/thesis-assesor-seth-chandler .claude/skills/thesis-assesor && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "thesis-assesor" agent skill from https://github.com/lawve-ai/awesome-legal-skills/tree/main/skills/thesis-assesor-seth-chandler into .claude/skills/thesis-assesor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "thesis-assesor", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/lawve-ai/awesome-legal-skills/tree/main/skills/thesis-assesor-seth-chandlerType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add lawve-ai/awesome-legal-skills --skill thesis-assesor -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install lawve-ai/awesome-legal-skills thesis-assesor --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/lawve-ai/awesome-legal-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/thesis-assesor-seth-chandler .agents/skills/thesis-assesor && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "thesis-assesor" agent skill from https://github.com/lawve-ai/awesome-legal-skills/tree/main/skills/thesis-assesor-seth-chandler into .agents/skills/thesis-assesor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "thesis-assesor", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add lawve-ai/awesome-legal-skills --skill thesis-assesor -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install lawve-ai/awesome-legal-skills thesis-assesor --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/lawve-ai/awesome-legal-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/thesis-assesor-seth-chandler .cursor/skills/thesis-assesor && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "thesis-assesor" agent skill from https://github.com/lawve-ai/awesome-legal-skills/tree/main/skills/thesis-assesor-seth-chandler into .cursor/skills/thesis-assesor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "thesis-assesor", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/lawve-ai/awesome-legal-skills.git --path skills/thesis-assesor-seth-chandler--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add lawve-ai/awesome-legal-skills --skill thesis-assesor -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install lawve-ai/awesome-legal-skills thesis-assesor --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/lawve-ai/awesome-legal-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/thesis-assesor-seth-chandler .gemini/skills/thesis-assesor && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "thesis-assesor" agent skill from https://github.com/lawve-ai/awesome-legal-skills/tree/main/skills/thesis-assesor-seth-chandler into .gemini/skills/thesis-assesor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "thesis-assesor", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install lawve-ai/awesome-legal-skills thesis-assesorInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add lawve-ai/awesome-legal-skills --skill thesis-assesor -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/lawve-ai/awesome-legal-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/thesis-assesor-seth-chandler .github/skills/thesis-assesor && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "thesis-assesor" agent skill from https://github.com/lawve-ai/awesome-legal-skills/tree/main/skills/thesis-assesor-seth-chandler into .github/skills/thesis-assesor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "thesis-assesor", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add lawve-ai/awesome-legal-skills --skill thesis-assesor -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install lawve-ai/awesome-legal-skills thesis-assesor --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/lawve-ai/awesome-legal-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/thesis-assesor-seth-chandler .opencode/skills/thesis-assesor && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "thesis-assesor" agent skill from https://github.com/lawve-ai/awesome-legal-skills/tree/main/skills/thesis-assesor-seth-chandler into .opencode/skills/thesis-assesor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "thesis-assesor", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
thesis-assesorCritically assess and improve a legal scholarly thesis, article idea, student note, seminar-paper claim, or research agenda using Eugene Volokh's novelty, nonobviousness, utility, and soundness…
Thesis Assesor is an agent skill from lawve-ai/awesome-legal-skills. Critically assess and improve a legal scholarly thesis, article idea, student note, seminar-paper claim, or research agenda using Eugene Volokh's novelty, nonobviousness, utility, and soundness framework, connector-aware research, claim-specific tests, and a sustainable adversarial pass. Produces a self-contained green-, yellow-, or red-light report. Use when a law professor or law student asks whether a claim is viable, novel, publishable, preempted, useful, worth pursuing, or better than competing topics; or…
Its SKILL.md is about 4.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files (for example `README.md`, `resources/research-routing.md` and `resources/test-suites-by-claim-type.md`).
It sits in Education, covering Essays and academic help. The repository describes itself as: A curated list of awesome Agent Skills for automating legal work. The licence is Apache-2.0.
7 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 045f738. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Thesis Assesor loads about 4.2k tokens when it runs. Until then it costs about 186 tokens; SKILL.md has 2,143 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from lawve-ai/awesome-legal-skills at commit 045f738, republished under its Apache-2.0 licence (© lawve-ai). 2,143 words, ~4,244 tokens.
.claude/skills/thesis-assesor/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.Assess legal scholarship candidly and proportionately. Derive the core criteria from Eugene Volokh's Academic Legal Writing, but adapt the research, tests, and deliverable to the author's role, claim type, jurisdiction, and available research capabilities. Do not confuse encouragement with evaluation.
Infer the mode from context when possible. Ask only when the answer would materially change the work and a reasonable assumption would be risky.
Identify the principal contribution type: doctrinal, normative, empirical, historical, theoretical, taxonomic, interpretive, comparative, or mixed. Use that classification to choose sources and stress tests.
State the best assessable version before judging it:
For a rough idea, propose a provisional crystallization and label its assumptions. Do not force historical, theoretical, or taxonomic work into a litigation-remedy template.
Test whether the thesis is identifiable, researchable, and plausibly distinct from the most obvious prior work. If it is fully preempted or incoherent at this level, explain the decisive problem and offer pivots before spending the full research budget on hypotheticals or remote issues. Continue with a full assessment when the user requests one despite the screen.
Before researching, inspect the tools available in the current session. Check both the immediately visible tools and any searchable, deferred, lazy-loaded, plugin, app, or connector inventory the host exposes. If the host provides tool search or another discovery mechanism, search by capability rather than product name:
Treat product names as illustrative, never exhaustive. Distinguish visible, installed, connected, authenticated, authorized, and functioning. Follow each selected tool's own instructions, including full-record retrieval or opinion analysis before citation. Do not ask the user to enumerate connectors before inspecting what is available.
If the user names a connector, database, library, or source, search the discoverable inventory for that name as well as its capability and attempt to use it if it is functioning. Do not silently substitute another source or decline to use the named source merely because a different source seems better. Use the named source for the questions it can answer, supplement it where necessary, and report any genuine limitation.
Read resources/research-routing.md whenever research is required. Use public primary
sources, institutional repositories, and web research when no suitable connector is usable.
Ask about access only when a missing proprietary collection could materially change the
verdict or the user specifically requested it. Record the fallback and lower confidence when
warranted.
Treat novelty and soundness as research questions, not memory tests.
Never call a claim definitively novel merely because a diligent search found no preemption. Say: No preemption located in the sources searched as of [date], then identify the search limits and remaining work.
Rate each criterion PASS, NEEDS WORK, or FAIL, and add high, moderate, or low confidence. Explain the decisive evidence and give a concrete repair for anything short of PASS.
Ask whether prior work makes materially the same claim for materially the same reasons. Distinguish topic novelty from claim novelty and classify the research:
Use a compact preemption matrix for important sources: thesis, mechanism or method, evidence, scope, payoff, and remaining difference.
Ask whether the thesis teaches a competent reader something beyond the straightforward application of familiar doctrine or a predictable policy preference. Credit hidden mechanisms, surprising implications, reconciliations of accepted principles, new evidence, new explanatory tools, and demonstrations that alter the conventional account. Keep this distinct from novelty: novelty asks whether the claim exists; nonobviousness asks whether the inferential step is worth learning.
Identify the audience and concrete payoff. For practical or doctrinal work, identify the decision, proceeding, drafting choice, institutional practice, or remedy that changes and a plausible first adopter. For historical, theoretical, taxonomic, or interpretive work, identify the mistaken understanding displaced, the category clarified, the debate reorganized, or the research program enabled. Flag claims with no implementation path, unavailable informational requirements, or no plausible audience.
Separate and test:
Apply principles across political or normative valences. Do not manufacture a partisan mirror when none exists; use symmetry, role reversal, or an equivalent consistency test.
Read resources/test-suites-by-claim-type.md and select the smallest set of tests that can
expose the claim's material weaknesses. Use five to seven tests for a mature doctrinal or
normative thesis; use fewer for an early screen and substitute method-appropriate tests for
empirical, historical, theoretical, comparative, or taxonomic claims. For each test, state
the scenario or challenge, apply the thesis, and judge whether the result is acceptable.
Do not depend on another skill. If sustainable-opposing-counsel-review is already available
and the host can combine skills, use its double-pass discipline internally only. Do not
inherit its advocacy-oriented output structure or its instruction to avoid balanced merits
assessment. If it is unavailable, perform this pass directly:
The deliverable contains only the surviving objections, not the discarded first pass.
Do not mechanically average ratings. Novelty and soundness can be dispositive. A FAIL means the core must change, not merely that further research would be useful. After repeated revisions leave the same defect intact, recommend a new angle.
Use this default structure, shortening it for an expressly requested quick screen:
The default deliverable is one complete, self-contained report. Do not finish a requested full assessment with only a verdict, progress note, connector addendum, or list of sources. If later research materially changes the assessment, reissue or update the consolidated report rather than making the user reconstruct it from successive messages. Before delivery, verify that all eight sections are present or expressly marked inapplicable.
For a substantial assessment, when the host provides a user-accessible filesystem or artifact mechanism, save a durable Markdown copy and link or attach it in the final response. If the host cannot create files, provide the complete report in the final response. A saved file supplements, and does not replace, a clear bottom-line handoff.
For a student, make the next steps manageable and name questions worth taking to an adviser. For a professor, emphasize interlocutors, contribution positioning, methodological burdens, and publication risk. For multiple topics, use the same criteria and comparable research effort, then rank them without false numerical precision.
Write natural, direct prose. If the user requests a Word document, use the available document creation skill and preserve the same substance in a polished scorecard.
resources/research-routing.md — read whenever external research is required; it governs
connector discovery, source hierarchy, preemption searching, fallbacks, and the research
record.resources/test-suites-by-claim-type.md — read before selecting tests; it supplies modular
suites for doctrinal, normative, empirical, historical, theoretical, taxonomic,
interpretive, and comparative claims.This skill is a research and scholarly-development aid, not legal advice, a citator, or a guarantee of publication. Its verdict depends on the sources the host can reach, the quality of the user's thesis, and the time and search coverage available.
Connector discovery is host-dependent. A host may expose only some installed tools, may hide lazy-loaded connectors, or may require authentication the skill cannot supply. The skill must use its fallback ladder and disclose the resulting coverage; it must never turn a failed search into proof of novelty.
Academic indexes do not comprehensively cover law reviews, working papers, books, foreign-law sources, or very recent drafts. Legal connectors and public repositories may omit dockets, unpublished opinions, citator treatment, or paywalled scholarship. Controlling law, quotations, and publication-critical novelty claims require independent professional verification.
The method transfers across jurisdictions, but the governing law does not. The user or agent must identify the relevant jurisdiction, hierarchy of authority, and research sources for each assessment. A jurisdiction value of “All” describes the method's portability, not universal substantive-law coverage.
A saved report is available only when the host provides a user-accessible file or artifact mechanism. Otherwise the complete report must be delivered in the conversation.
This package contains no executable code and makes no network calls itself. Any research access comes from capabilities supplied and controlled by the host.
Attribute the four-criterion framework and test-suite method to Eugene Volokh, Academic Legal Writing: Law Review Articles, Student Notes, Seminar Papers, and Getting on Law Review (5th ed. 2016), ISBN 978-1-63459-888-0, and Eugene Volokh, “Test Suites: A Tool for Improving Student Articles,” 52 Journal of Legal Education 440 (2002).
This skill derives from volokh-claim-assessor and adapts the double-pass sustainability
discipline of sustainable-opposing-counsel-review for balanced scholarly assessment.
Those references identify intellectual and workflow influences; they do not imply endorsement
by Eugene Volokh or by the authors of any companion skill.
© lawve-ai, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 5 other files in skills/thesis-assesor-seth-chandler of lawve-ai/awesome-legal-skills.
Open the folder on GitHubat commit 045f738
Thesis Assesor next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Thesis Assesor this skilllawve-ai/awesome-legal-skills | 847 | — | ~4.2k | Automated safety check: Pass | Apache-2.0 | |
| Academic Paper StrategistAAASS554/codex-academic-paper-skills | 539 | 1 repos | ~2.7k | Automated safety check: Pass | MIT | |
| Modeling Paper Rubric and Model Selectoryushui2022/MathModel-Skill | 454 | 1 repos | ~1.8k | Automated safety check: Pass | MIT | |
| Humanities Thesisganzhi-black/humanities-thesis-skill | 637 | — | ~1.7k | Automated safety check: Pass | MIT | |
| Skill Thesis Writeryanlin-cheng/skill-thesis-writer | 209 | — | ~1.6k | Automated safety check: Pass | Custom licence | |
| Thesis CreatorStars-OC/thesis-creator | 230 | — | ~2.8k | Automated safety check: Pass | MIT |
AAASS554/codex-academic-paper-skills
A skill your agent uses when the user needs to plan, de-risk, or ground a software engineering / computer science undergraduate thesis from a real codebase before final writing.
yushui2022/MathModel-Skill
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ganzhi-black/humanities-thesis-skill
人文社科论文写作全流程指导。适用于文学、历史、哲学、社会学、传播学、新闻学、文化研究等领域的中文学术论文。当用户提到"论文""写论文""选题""文献综述""论文修改""论文结构""摘要翻译""帮我查文献""参考文献格式""论文没有新意""理论和文本脱节""章节之间缺乏逻辑""帮我检查论文""摘要翻译成英文""投稿准备""脚注格式"等场景时触发。覆盖从选题到投稿的全流程,包含防幻觉规则、学术数据库…
yanlin-cheng/skill-thesis-writer
跨学科AI论文写作助手,专为本科生/研究生论文写作提供全方位支持。当用户需要撰写论文内容、设计论文框架结构、优化学术语体风格、处理参考文献格式(GB/T 7714-2015)、生成统计分析表格、或降低AI生成文本痕迹时使用此技能。支持工科(计算机/电子/机械等)、心理学、教育学、管理学等多学科领域,符合中国学术论文写作规范。
Stars-OC/thesis-creator
Walks Chinese undergraduates through writing a graduation thesis from topic to Word export, with text-similarity reduction and AI-text rate rewriting and checks.
free-revalution/AIGC-Detector-Pro
Academic paper AI content detection, rewriting, and thesis writing assistant.
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Categories
Critically assess and improve a legal scholarly thesis, article idea, student note, seminar-paper claim, or research agenda using Eugene Volokh's novelty, nonobviousness, utility, and soundness…. Thesis Assesor is an agent skill from lawve-ai/awesome-legal-skills. Critically assess and improve a legal scholarly thesis, article idea, student note, seminar-paper claim, or research agenda using Eugene Volokh's novelty, nonobviousness, utility, and soundness framework, connector-aware research, claim-specific tests, and a sustainable adversarial pass.
Thesis Assesor fits situations like: A law professor; law student asks whether a claim is viable; better than competing topics; wants a thesis stress-tested.
Run `npx skills add lawve-ai/awesome-legal-skills --skill thesis-assesor -a claude-code`. Or copy the skill folder (skills/thesis-assesor-seth-chandler in lawve-ai/awesome-legal-skills) into .claude/skills/thesis-assesor in your project. Claude Code loads it when a task matches its description.
Run `npx skills add lawve-ai/awesome-legal-skills --skill thesis-assesor -a codex`. Or copy the skill folder (skills/thesis-assesor-seth-chandler in lawve-ai/awesome-legal-skills) into .agents/skills/thesis-assesor in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add lawve-ai/awesome-legal-skills --skill thesis-assesor -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/thesis-assesor, .gemini/skills/thesis-assesor, .github/skills/thesis-assesor and .opencode/skills/thesis-assesor in your project.
SKILL.md names no scripts, command-line tools or credentials: Thesis Assesor is instructions for the agent only.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Thesis Assesor is published under the Apache-2.0 licence (from the LICENSE file in the skill folder). It allows redistribution, so the full SKILL.md is shown on this page.
About 4.2k tokens (SKILL.md is roughly 17k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Thesis Assesor: Academic Paper Strategist (AAASS554/codex-academic-paper-skills, 539 stars), Modeling Paper Rubric and Model Selector (yushui2022/MathModel-Skill, 454 stars), Humanities Thesis (ganzhi-black/humanities-thesis-skill, 637 stars) and Skill Thesis Writer (yanlin-cheng/skill-thesis-writer, 209 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
lawve-ai (a GitHub organization) maintains it in lawve-ai/awesome-legal-skills, which has 847 GitHub stars. The repository holds 154 skills in this directory. The repository was last updated on October 2, 2026.
Source: lawve-ai/awesome-legal-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.