Integration Theory
parcadei/Continuous-Claude-v3
Problem-solving strategies for integration theory in measure theory
A skill your agent uses when a The Journal of Law and Economics (JLE) manuscript needs a model of the legal rule — deterrence, liability, contracting, or regulation — to interpret estimates…
MITAuto-check passed
Install Jle Theory Model
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jle-theory-model -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jle-theory-model --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/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/Journal-of-Law-and-Economics-Skills/skills/jle-theory-model .claude/skills/jle-theory-model && 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 "jle-theory-model" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Law-and-Economics-Skills/skills/jle-theory-model into .claude/skills/jle-theory-model/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jle-theory-model", 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/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Law-and-Economics-Skills/skills/jle-theory-modelType 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 brycewang-stanford/Awesome-Journal-Skills --skill jle-theory-model -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jle-theory-model --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/Journal-of-Law-and-Economics-Skills/skills/jle-theory-model .agents/skills/jle-theory-model && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "jle-theory-model" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Law-and-Economics-Skills/skills/jle-theory-model into .agents/skills/jle-theory-model/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jle-theory-model", 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 brycewang-stanford/Awesome-Journal-Skills --skill jle-theory-model -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jle-theory-model --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/Journal-of-Law-and-Economics-Skills/skills/jle-theory-model .cursor/skills/jle-theory-model && 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 "jle-theory-model" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Law-and-Economics-Skills/skills/jle-theory-model into .cursor/skills/jle-theory-model/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jle-theory-model", 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/brycewang-stanford/Awesome-Journal-Skills.git --path Journal-of-Law-and-Economics-Skills/skills/jle-theory-model--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 brycewang-stanford/Awesome-Journal-Skills --skill jle-theory-model -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jle-theory-model --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/Journal-of-Law-and-Economics-Skills/skills/jle-theory-model .gemini/skills/jle-theory-model && 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 "jle-theory-model" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Law-and-Economics-Skills/skills/jle-theory-model into .gemini/skills/jle-theory-model/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jle-theory-model", 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 brycewang-stanford/Awesome-Journal-Skills jle-theory-modelInstalls 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 brycewang-stanford/Awesome-Journal-Skills --skill jle-theory-model -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/Journal-of-Law-and-Economics-Skills/skills/jle-theory-model .github/skills/jle-theory-model && 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 "jle-theory-model" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Law-and-Economics-Skills/skills/jle-theory-model into .github/skills/jle-theory-model/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jle-theory-model", 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 brycewang-stanford/Awesome-Journal-Skills --skill jle-theory-model -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jle-theory-model --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/Journal-of-Law-and-Economics-Skills/skills/jle-theory-model .opencode/skills/jle-theory-model && 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 "jle-theory-model" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Law-and-Economics-Skills/skills/jle-theory-model into .opencode/skills/jle-theory-model/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jle-theory-model", 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.
Facts
- Skill name
jle-theory-model- GitHub stars
- 1.2k
- Token cost
- ~2.3k tokens
- SKILL.md length
- 1,146 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when a The Journal of Law and Economics (JLE) manuscript needs a model of the legal rule — deterrence, liability, contracting, or regulation — to interpret estimates…
- Works in 5 steps: Make the legal rule a primitive. The… → Comparative statics before estimates.… → Sufficient statistics where possible.… → …
- A The Journal of Law and Economics (JLE) manuscript needs a model of the legal rule — deterrence
- SKILL.md covers When to trigger, The JLE theory tradition, Modeling craft and Canonical JLE modeling…, plus 6 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Jle Theory Model is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when a The Journal of Law and Economics (JLE) manuscript needs a model of the legal rule — deterrence, liability, contracting, or regulation — to interpret estimates, generate testable predictions, or carry a theory contribution in the Chicago price-theory tradition. Calibrates how much theory belongs and where; it does not design the identification (jle-identification).
Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
The repository describes itself as: Journal-specific Claude Code/Codex skill packs covering mainstream journals — AER, QJE, Nature, Cell, 管理世界, 经济研究 & 200+ more — your fast track to getting published. ｜ 覆盖主流期刊的… The licence is MIT.
When your agent uses it
- A The Journal of Law and Economics (JLE) manuscript needs a model of the legal rule — deterrence
- Regulation — to interpret estimates
- Generate testable predictions
- Carry a theory contribution in the Chicago price-theory tradition
Example prompts
- “/jle-theory-model”
Workflow steps
5 steps, taken from the first numbered list in SKILL.md.
- Make the legal rule a primitive. The penalty schedule, the liability standard, the entitlement, the enforcement probability should be…
- Comparative statics before estimates. Derive the sign predictions about the rule first; test them after. Predictions invented post hoc…
- Sufficient statistics where possible. Express the welfare/optimal-rule object as a function of estimable elasticities (deterrence…
- Tie any structural parameter to the institution. If you do estimate a model, each parameter should map to a data feature and a legal…
- State scope and what the model omits — general-equilibrium feedbacks, enforcement endogeneity, behavioral departures from rational…
What it can do on your machine
Read from SKILL.md and the folder at commit 932eb23. 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
Jle Theory Model loads about 2.3k tokens when it runs. Until then it costs about 99 tokens; SKILL.md has 1,146 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.
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 brycewang-stanford/Awesome-Journal-Skills at commit 932eb23, republished under its MIT licence (© brycewang-stanford). 1,146 words, ~2,289 tokens.
Download SKILL.mdSave it as
.claude/skills/jle-theory-model/SKILL.md (or your agent's skills folder).- name
- jle-theory-model
- description
- Use when a The Journal of Law and Economics (JLE) manuscript needs a model of the legal rule — deterrence, liability, contracting, or regulation — to interpret estimates, generate testable predictions, or carry a theory contribution in the Chicago price-theory tradition. Calibrates how much theory belongs and where; it does not design the identification (jle-identification).
Theory & Model of the Legal Rule (jle-theory-model)
When to trigger
- A referee asks "what is the economic mechanism / what model rationalizes this legal effect?"
- A reduced-form effect of a rule is credible but its economic meaning (deterrence vs. incapacitation, price vs. quality) is ambiguous
- You want a welfare statement about a legal rule, an optimal-penalty result, or a comparative static the raw estimate cannot deliver
- The paper is theoretical and you need its predictions about a legal rule to be recognizable and testable, not decorative
The JLE theory tradition
JLE's theory is price theory applied to legal rules — Becker on crime (expected punishment = probability × severity), Coase on bargaining and entitlements, Calabresi/Posner on liability and least-cost avoidance, Stigler/Peltzman on regulation and capture, the litigation-selection logic of Priest–Klein. Theory earns its place when it names the mechanism, maps a coefficient to a structural object, delivers a welfare or optimal-rule result, or generates a comparative static you then test. JLE accepts genuinely theoretical papers, but even pure theory should speak about a legal institution a reader can recognize. Pick the lightest tool that does the job; do not let a model silently replace the identification an empirical design provided.
| Theory's job | Right amount of model | Where it goes |
|---|---|---|
| Name the mechanism behind a legal effect | a few equations / a deterrence or bargaining sketch | short framework before results |
| Map a reduced-form coefficient to a structural object (elasticity of crime to expected punishment) | a sufficient-statistic / first-order condition | inline derivation + appendix |
| Deliver a welfare or optimal-penalty result | a calibrated or partial-equilibrium model of the rule | a dedicated, bounded section |
| Generate sign/comparative-static predictions about a rule | a simple model of the legal game | framework section, tested in results |
| Carry a standalone theory contribution | a fully solved model of a legal institution | the body of the paper, with empirical/illustrative discipline |
Modeling craft
- Make the legal rule a primitive. The penalty schedule, the liability standard, the entitlement, the enforcement probability should be objects in the model, not afterthoughts — that is what makes it law-and-economics rather than generic theory.
- Comparative statics before estimates. Derive the sign predictions about the rule first; test them after. Predictions invented post hoc read as HARKing the theory.
- Sufficient statistics where possible. Express the welfare/optimal-rule object as a function of estimable elasticities (deterrence elasticity, demand response to a penalty) rather than estimating a full structural model — credibility stays in the design.
- Tie any structural parameter to the institution. If you do estimate a model, each parameter should map to a data feature and a legal mechanism, validated against an untargeted moment.
- State scope and what the model omits — general-equilibrium feedbacks, enforcement endogeneity, behavioral departures from rational deterrence.
Canonical JLE modeling templates (reach for the closest)
Rather than build from scratch, most JLE theory contributions extend one of a few canonical frames. Name the one you are using; referees recognize them and will judge your extension against them.
- Deterrence (Becker): expected punishment = probability of apprehension × severity; offenders respond to the margin. Use for crime, enforcement, regulatory penalties, tax evasion. The comparative static you usually want: how an outcome moves with the expected (not nominal) penalty.
- Liability / least-cost avoider (Calabresi–Posner): negligence vs. strict liability allocate care between injurer and victim; the efficient rule minimizes the sum of accident and avoidance costs. Use for torts, products liability, accidents.
- Bargaining & entitlements (Coase): with low transaction costs the efficient outcome is invariant to the entitlement; with frictions the rule matters. Use for property, nuisance, contract remedies.
- Regulation & capture (Stigler–Peltzman): regulation is supplied to politically organized groups; the regulator trades off producer and consumer support. Use for entry licensing, rate regulation, occupational rules.
- Litigation selection (Priest–Klein): which disputes settle vs. go to trial is endogenous, so trial samples are selected. Use whenever you study court outcomes — it warns against reading trial win-rates naively.
Checklist
- Theory's job named (mechanism / mapping / welfare-or-optimal-rule / comparative statics / standalone)
- The legal rule (penalty, standard, entitlement, enforcement) is a primitive in the model
- Lightest adequate tool chosen; for empirical papers, the model does not upstage the design
- If a sufficient statistic: the estimable elasticities and validity assumptions stated
- If structural: each parameter tied to a data feature and a legal mechanism; untargeted-moment validation
- Comparative statics / sign predictions derived before they are tested
- Welfare/optimal-rule numbers carry uncertainty and a stated scope (what is omitted)
Show full SKILL.md (426 more words)Show less
Anti-patterns
- A "model" that adds notation but no testable prediction about the legal rule
- Comparative statics produced after seeing the results (HARKing the theory)
- Letting model assumptions quietly substitute for the identification the empirical design should provide
- A welfare or optimal-penalty number with no uncertainty and no statement of omissions
- Generic mechanism-design theory with no recognizable legal institution (drifts toward a theory journal)
Worked vignette (illustrative)
A clean RD shows a sentence-enhancement threshold cuts re-offending by 5pp (s.e. 1.4). The number is credible but the policy question is whether harsher sentences deter or merely incapacitate. Instead of a full dynamic crime model, the paper uses a Becker-style framework: the deterrence channel predicts a drop in new offenses by those still at liberty near the margin, while incapacitation predicts a drop only during custody. A sufficient-statistic argument expresses the marginal deterrence value as the offense elasticity to expected punishment (estimated from the RD) times the social cost per offense (calibrated). The framework yields a testable split the paper then confirms in the timing of effects — the JLE ideal of theory that names and tests a legal mechanism.
How much theory is too much for an empirical JLE paper
JLE publishes both empirical and theoretical work, so the dial is wider than at an empirical-only journal — but for an empirical submission the model should still stay in its lane:
- Too little: a reduced-form effect with no framework, leaving the referee to ask "deterrence or incapacitation? price or quality?" with no way to tell.
- Right: a compact framework that issues a sign or comparative-static prediction the data then adjudicate, plus (if needed) a sufficient-statistic mapping to a welfare or optimal-rule number.
- Too much: a fully solved structural model whose assumptions, not the legal variation, now carry the identification — at which point reviewers ask why the empirical design was needed at all.
For a theoretical submission the calculus inverts: the model is the contribution, but it must still concern a recognizable legal institution and yield results an empiricist could in principle confront with data.
Referee pushback mapped to the theory fix
- "What is the mechanism behind this legal effect?" → Add a short framework (deterrence / liability / bargaining) with a sign prediction you then test — not more notation.
- "This number is not policy-relevant without a welfare statement." → Express the optimal-rule object as a sufficient statistic of estimable elasticities; state the validity assumptions.
- "Your model just assumes the result." → Make the legal rule a primitive, tie each parameter to a data feature and a mechanism, and validate against an untargeted moment.
Output format
【Theory's job】mechanism / coefficient-to-structural mapping / welfare-or-optimal-rule / comparative statics / standalone
【Legal rule as primitive】penalty / standard / entitlement / enforcement: ___
【Tool chosen】framework / sufficient statistic / small structural model / fully solved model
【Key relation】estimand = f(estimable elasticities / parameters): ___
【Predictions derived before testing】[Y/N]
【Validity + what it omits】[...]
【Next step】jle-robustness© brycewang-stanford, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in Journal-of-Law-and-Economics-Skills/skills/jle-theory-model of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Jle Theory Model 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 |
|---|---|---|---|---|---|---|
| Jle Theory Model this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~2.3k | Automated safety check: Pass | MIT | |
| Integration Theoryparcadei/Continuous-Claude-v3 | 3.9k | 1 repos | ~929 | Automated safety check: Notes | MIT | |
| Asymptotic Theorybrycewang-stanford/Auto-Empirical-Research-Skills | 4.6k | — | ~4.6k | Automated safety check: Pass | Custom licence | |
| Operator Theoryparcadei/Continuous-Claude-v3 | 3.9k | 1 repos | ~879 | Automated safety check: Notes | MIT | |
| Proof Theoryparcadei/Continuous-Claude-v3 | 3.9k | 1 repos | ~452 | Automated safety check: Notes | MIT | |
| Writing LawNorman-bury/research-writing-skill | 3.4k | — | ~592 | Automated safety check: Pass | MIT |
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Questions about Jle Theory Model
What does Jle Theory Model do?
A skill your agent uses when a The Journal of Law and Economics (JLE) manuscript needs a model of the legal rule — deterrence, liability, contracting, or regulation — to interpret estimates…. Jle Theory Model is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when a The Journal of Law and Economics (JLE) manuscript needs a model of the legal rule — deterrence, liability, contracting, or regulation — to interpret estimates, generate testable predictions, or carry a theory contribution in the Chicago price-theory tradition.
When should I use Jle Theory Model?
Jle Theory Model fits situations like: A The Journal of Law and Economics (JLE) manuscript needs a model of the legal rule — deterrence; regulation — to interpret estimates; generate testable predictions; carry a theory contribution in the Chicago price-theory tradition.
How do I install Jle Theory Model in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jle-theory-model -a claude-code`. Or copy the skill folder (Journal-of-Law-and-Economics-Skills/skills/jle-theory-model in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/jle-theory-model in your project. Claude Code loads it when a task matches its description.
How do I install Jle Theory Model in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jle-theory-model -a codex`. Or copy the skill folder (Journal-of-Law-and-Economics-Skills/skills/jle-theory-model in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/jle-theory-model in your project. Codex loads it when a task matches its description.
Can I use Jle Theory Model 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 brycewang-stanford/Awesome-Journal-Skills --skill jle-theory-model -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/jle-theory-model, .gemini/skills/jle-theory-model, .github/skills/jle-theory-model and .opencode/skills/jle-theory-model in your project.
What does Jle Theory Model need to run?
SKILL.md names no scripts, command-line tools or credentials: Jle Theory Model is instructions for the agent only.
Does Jle Theory Model 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 Jle Theory Model 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 Jle Theory Model use?
Jle Theory Model is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Jle Theory Model use?
About 2.3k tokens (SKILL.md is roughly 9.2k 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 Jle Theory Model?
Skills that share tags, products or a category with Jle Theory Model: Integration Theory (parcadei/Continuous-Claude-v3, 3.9k stars), Asymptotic Theory (brycewang-stanford/Auto-Empirical-Research-Skills, 4.6k stars), Operator Theory (parcadei/Continuous-Claude-v3, 3.9k stars) and Proof Theory (parcadei/Continuous-Claude-v3, 3.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Jle Theory Model?
brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,231 GitHub stars. The repository holds 2,387 skills in this directory. The repository was last updated on September 27, 2026.
Source: brycewang-stanford/Awesome-Journal-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.