Agent skill

Thesis Assesor

by lawve-ai in 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…

Apache-2.0Auto-check passedEducation

Install Thesis Assesor

skills CLI
$ npx skills add lawve-ai/awesome-legal-skills --skill thesis-assesor -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install lawve-ai/awesome-legal-skills thesis-assesor --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ 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-src

Use ~/.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/

Facts

Skill name
thesis-assesor
GitHub stars
847
Token cost
~4.2k tokens
SKILL.md length
2,143 words
Files
6
Skills in repo
154
Repo updated
First seen
Licence
Apache-2.0

At a glance

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…

  • Works in 7 steps: Screen → Discover and route research capabilities → Research before judging → …
  • A law professor
  • SKILL.md covers Establish the assessment mode, Crystallize the claim, Stage the assessment and Apply the Volokh criteria, plus 7 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

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.

When your agent uses it

  • A law professor
  • Law student asks whether a claim is viable
  • Better than competing topics
  • Wants a thesis stress-tested

Example prompts

  • “/thesis-assesor”

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. Screen
  2. Discover and route research capabilities
  3. Research before judging
  4. Novelty
  5. Nonobviousness
  6. Utility
  7. Soundness

What it can do on your machine

Read from SKILL.md and the folder at commit 045f738. It shows what the files ask for, not the result of running them.

  • Tool permissions

    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.

  • Runs code

    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.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

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.

Always · name and description, kept in context so the agent knows when to use it
~186
When it runs · the whole SKILL.md, loaded when a task matches
~4.2k

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.

Safety

Auto-check passed

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.

SKILL.md

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.

Download SKILL.mdSave it as .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.
name
thesis-assesor
description
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 wants a thesis stress-tested, narrowed, repaired, or compared. No connector is required: use connected legal and scholarly research when available, public sources otherwise, and disclose any no-research fallback.
metadata.author
Seth J. Chandler
metadata.author_link
https://legaled.ai
metadata.license
Apache-2.0
metadata.version
2026-08-29
metadata.jurisdiction
All
metadata.language
English
metadata.category
legal-education
metadata.derived_from
volokh-claim-assessor and Eugene Volokh's published academic-writing framework

Thesis Assessor

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.

Establish the assessment mode

Infer the mode from context when possible. Ask only when the answer would materially change the work and a reasonable assumption would be risky.

  • Professor article or book project: demand a publication-grade contribution map, identify the closest scholarly interlocutors, test the method, and state what experts would learn.
  • Student note: emphasize claim novelty, manageable scope, accessible authority, a credible contribution beyond summary, and a path to completion and possible publication.
  • Seminar paper: identify the minimum viable claim, fit the scope to the assignment and available time, and prioritize the next research and writing moves.
  • Exploratory idea or competing topics: conduct a staged screen, spend comparable research effort on each candidate, rank them, and explain the decisive differences.

Identify the principal contribution type: doctrinal, normative, empirical, historical, theoretical, taxonomic, interpretive, comparative, or mixed. Use that classification to choose sources and stress tests.

Crystallize the claim

State the best assessable version before judging it:

  1. Thesis — the proposition the paper will establish, not merely its subject.
  2. Contribution — what the thesis adds to the closest existing account.
  3. Payoff — what a reader, institution, decisionmaker, or field would understand or do differently if the thesis is right.
  4. Warrant or method — the doctrine, evidence, history, theory, comparison, or mechanism that supports the thesis.
  5. Scope — jurisdiction, time period, institutions, actors, and boundary conditions.

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.

Stage the assessment

Stage 1 — Screen

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.

Stage 2 — Discover and route research capabilities

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:

  1. primary law, citator, and case-status research;
  2. legal scholarship, working papers, and authoritative secondary sources;
  3. peer-reviewed empirical or interdisciplinary research;
  4. legislation, regulations, government data, and authoritative records; and
  5. the user's own library or document corpus, when relevant and authorized.

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.

Stage 3 — Research before judging

Treat novelty and soundness as research questions, not memory tests.

  • Search multiple formulations of the thesis, contribution, mechanism, doctrinal label, and likely opposing terminology. Search forthcoming work and recent developments.
  • For a full professor-article or publication-grade assessment, use at least one available academic-paper, scholarly-index, or user-library connector as a supplementary preemption search. Academic indexes may surface older law-review and interdisciplinary work even when their principal description emphasizes scientific or peer-reviewed literature. Do not use them as substitutes for primary-law verification or a comprehensive legal-scholarship search.
  • Read enough of each important source to determine its actual thesis and reasoning. Never classify preemption or support from a title or snippet alone.
  • Verify controlling law, adverse authority, quotations, and current case status through primary sources or a suitable legal-research tool.
  • Use empirical research tools for empirical premises, not as substitutes for searching law reviews, legal working papers, or primary law.
  • Distinguish facts, inferences, predictions, causal claims, and normative premises.
  • Cite material sources with working links and disclose meaningful access limits.

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.

Apply the Volokh criteria

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.

1. Novelty

Ask whether prior work makes materially the same claim for materially the same reasons. Distinguish topic novelty from claim novelty and classify the research:

  • Fully preempted: the same core thesis and warrant already exist. Ordinarily FAIL.
  • Partially preempted: the thesis overlaps, but scope, mechanism, evidence, remedy, or synthesis may supply a defensible contribution. Usually NEEDS WORK.
  • Adjacent: the work addresses the field but differs materially in thesis or mechanism. It may provide an interlocutor rather than preemption.
  • No preemption located: provisional PASS only, with search limits.

Use a compact preemption matrix for important sources: thesis, mechanism or method, evidence, scope, payoff, and remaining difference.

2. Nonobviousness

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.

3. Utility

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.

4. Soundness

Separate and test:

  • legal soundness: current doctrine, hierarchy of authority, adverse law, and the line between description and proposal;
  • logical soundness: hidden premises, category errors, contradictions, and overclaims;
  • empirical soundness: measurement, identification, alternative explanations, source quality, and generalizability; and
  • institutional soundness: administrability, information constraints, incentives, strategic behavior, reliance, transition costs, and second-order effects.

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.

Run claim-type-specific tests

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.

Show full SKILL.md (912 more words)Show less

Run a sustainable scholarly red team

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:

  1. Generate three to five of the strongest fair objections to the thesis.
  2. State the author's best one-sentence reply to each objection.
  3. Ask whether the objection survives that reply and whether a serious scholar would lose credibility by pressing it.
  4. Discard objections based on conceded facts, speculation, wrong-forum rules, innocent discrepancies, overclaims, or points defeated by the obvious reply.
  5. Classify each surviving problem as fatal, reparable, or an unavoidable tradeoff, and identify the best repair or concession.

The deliverable contains only the surviving objections, not the discarded first pass.

Give the verdict and revision path

  • GREEN LIGHT: all four criteria are supportable and the claim survives the material tests. State remaining research and refinements.
  • YELLOW LIGHT: a viable core remains, but a specified change in scope, warrant, evidence, framing, or implementation is necessary. Supply a revised thesis and priorities.
  • RED LIGHT: novelty or soundness fails materially, or a core test exposes a fundamental defect. Explain why and propose concrete pivots or different claims in the same area.

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.

Present the result

Use this default structure, shortening it for an expressly requested quick screen:

  1. Claim as assessed — mode, contribution type, thesis, contribution, payoff, warrant, and scope.
  2. Bottom line — verdict, confidence, and decisive reason.
  3. Preemption map — closest work and material similarities and differences.
  4. Four-criteria assessment — rating, confidence, evidence, and repairs.
  5. Tests and sustainable objections — material results only.
  6. Best revision — revised thesis and contribution statement, or best pivot.
  7. Next research moves — prioritized and adapted to professor, note, or seminar mode.
  8. Research record — date, jurisdiction, tools and collections, representative queries, sources examined, access limits, and unresolved questions.

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.

Bundled resources

  • 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.

Limitations and risks

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.

Attribution and provenance

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

Files

SKILL.md and 5 other files in skills/thesis-assesor-seth-chandler of lawve-ai/awesome-legal-skills.

  • SKILL.md
  • LICENSE
  • NOTICE
  • README.md
  • resources/research-routing.md
  • resources/test-suites-by-claim-type.md

Open the folder on GitHubat commit 045f738

Compare with similar skills

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.

Thesis Assesor compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Thesis Assesor this skilllawve-ai/awesome-legal-skills847—~4.2kAutomated safety check: PassApache-2.0
Academic Paper StrategistAAASS554/codex-academic-paper-skills5391 repos~2.7kAutomated safety check: PassMIT
Modeling Paper Rubric and Model Selectoryushui2022/MathModel-Skill4541 repos~1.8kAutomated safety check: PassMIT
Humanities Thesisganzhi-black/humanities-thesis-skill637—~1.7kAutomated safety check: PassMIT
Skill Thesis Writeryanlin-cheng/skill-thesis-writer209—~1.6kAutomated safety check: PassCustom licence
Thesis CreatorStars-OC/thesis-creator230—~2.8kAutomated safety check: PassMIT

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Categories

Questions about Thesis Assesor

What does Thesis Assesor do?

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.

When should I use Thesis Assesor?

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.

How do I install Thesis Assesor in Claude Code?

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.

How do I install Thesis Assesor in Codex?

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.

Can I use Thesis Assesor in Cursor, Gemini CLI or GitHub Copilot?

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.

What does Thesis Assesor need to run?

SKILL.md names no scripts, command-line tools or credentials: Thesis Assesor is instructions for the agent only.

Does Thesis Assesor access the network?

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.

Is Thesis Assesor safe to install?

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.

What licence does Thesis Assesor use?

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.

How many tokens does Thesis Assesor use?

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.

What are the alternatives to Thesis Assesor?

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.

Who maintains Thesis Assesor?

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.