uk-court-of-appeal-judicial-preference-check

uk-court-of-appeal-judicial-preference-check is a skill for Claude Code, Codex from LegalQuants/lq-skills. It costs 69 tokens per session (2,276 once invoked), scanned A, original, Apache-2.0.

A review tool for testing England and Wales Court of Appeal drafts against drafting patterns visible in public judgments. It considers documents such as skeleton arguments, grounds of appeal, written submissions, and judgment-style memos.

In plain words
What is it for?
Use it to review appellate documents for structure, tone, level of detail, use of authorities, and balance between commercial context and legal principles.
Why use it?
It helps an appellate team identify writing that may be too factual, aggressive, lengthy, or focused on the wrong kind of reasoning. It provides drafting signals rather than predicting a judge's decision or replacing legal judgment.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to review appellate documents for structure, tone, level of detail, use of authorities, and balance between commercial context and legal principles.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/legalquants/lq-skills/uk-court-of-appeal-judicial-preference-check
Install

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.

Any agent
npx skills add LegalQuants/lq-skills --skill uk-court-of-appeal-judicial-preference-check
Clone the repo
git clone --depth 1 https://github.com/LegalQuants/lq-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for uk-court-of-appeal-judicial-preference-check

README.md
[![agentmods](https://agentmods.dev/badge/skills/legalquants/lq-skills/uk-court-of-appeal-judicial-preference-check/github.svg)](https://agentmods.dev/skills/legalquants/lq-skills/uk-court-of-appeal-judicial-preference-check)
Your own site
<a href="https://agentmods.dev/skills/legalquants/lq-skills/uk-court-of-appeal-judicial-preference-check"><img src="https://agentmods.dev/badge/skills/legalquants/lq-skills/uk-court-of-appeal-judicial-preference-check/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.

agentmods 80×15 button for uk-court-of-appeal-judicial-preference-check

Your own site · 80×15
<a href="https://agentmods.dev/skills/legalquants/lq-skills/uk-court-of-appeal-judicial-preference-check"><img src="https://agentmods.dev/badge/skills/legalquants/lq-skills/uk-court-of-appeal-judicial-preference-check.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 69 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,276 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00069 $0.02276
Opus 5 $0.00034 $0.01138
Sonnet 5 $0.00014 $0.00455
Haiku 4.5 $0.00007 $0.00228

Measured 12d ago against content hash d9297bc9bc6d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

uk-court-of-appeal-judicial-preference-check 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 12d 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.

skills/uk-court-of-appeal-judicial-preference-check/SKILL.md · 240 lines

How it starts

The opening of the file, as written. The whole thing — 240 lines — stays where its author put it; the contents beside it link to each section on GitHub.

uk-court-of-appeal-judicial-preference-check

When to Use

  • A user wants to test a draft against Court of Appeal style, expectations, and public-source judicial preference signals.
  • The document is a skeleton argument, grounds of appeal, respondent's notice, written submission, judgment-style memo, or appellate advice.
  • A panel or likely judge is known and the user wants source-backed drafting signals.
  • The user asks whether the draft reads too factual, too doctrinal, too aggressive, too long, too authority-heavy, too commercial, too black-letter, or insufficiently appellate.

This skill identifies source-backed drafting tendencies and judicial preference signals visible in public decisions. It does not predict votes, infer private judicial psychology, or replace counsel's advocacy judgment.

Audience and Work Shape

Audience: experienced appellate counsel, litigation solicitors, and supervised appellate teams drafting or reviewing England and Wales Court of Appeal materials.

Work shape: pattern-matched review of a draft against a public-source corpus, producing accretive judgment for counsel. It is not a transactional output and not for unsupervised self-represented use.

  • Legal support, not legal advice: the output is drafting-signal analysis, not advocacy strategy or merits advice.
  • Privilege/confidentiality: the draft may be privileged work product; use only approved environments and avoid unnecessary client-identifying detail in public-source searches.
  • Accountability: counsel owns the final drafting choices and any decision to adopt, reject, or ignore a signal.

Access Modes

This skill works in three modes:

  1. Live source mode - use browser, web search, MCP, API, or other configured access to retrieve public Court of Appeal decisions from Find Case Law, BAILII, court pages, or equivalent public sources.
  2. User-supplied source mode - use public judgments, URLs, PDFs, HTML, screenshots, exports, or pasted text supplied by the user.
  3. No-source mode - review the draft's internal appellate structure and prepare a research plan, but do not make source-backed judicial preference findings.

Read the full file on GitHub · 240 lines

Files

What ships with it

5 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.

Changes

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.

  1. 12d ago First seen · 240 lines · 69 tokens per session scan A d9297bc9bc6d

Subscribe to this mod's changes

uk-court-of-appeal-judicial-preference-check is a skill published in the GitHub repository LegalQuants/lq-skills (54 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 69 tokens to every session and 2,276 once invoked, about $0.0003 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 2026-08-30.

Related

Other skills, from other repositories

legaltech-expert

Expert in legal technology: contract lifecycle management, e-discovery, AI-assisted legal research, case and matter management, document automation, and compliance tooling. Use when the user mentions legal case or matter management, e-discovery and legal holds, CLM or contract review and obligation tracking, legal…

personamanagmentlayer/pcl · 74 tokens

deslop

Audits and rewrites legal writing, professional documentation, and general text to follow plain English principles. Translates archaic legalese and eliminates verbose "AI slop" by enforcing active voice, subject-verb proximity, and concise phrasing (inspired by Bryan Garner, the SEC Plain English Handbook, Federal…

fayerman-source/deslop · 85 tokens

Brief Section Drafter

Use when drafting a single section of a litigation brief — such as a statement of facts, argument section, standard of review, or conclusion — that is cited to the record, consistent with the case theory, and fully flagged for attorney verification before filing.

zgbrenner/agentcounsel · 55 tokens

Demand Letter

Use when drafting a demand letter for attorney review — running a structured intake, a pre-draft risk gate, and a draft with every legal conclusion, damages figure, and deadline flagged for attorney confirmation before sending.

zgbrenner/agentcounsel · 45 tokens

Litigation Chronology

Use when building a factual timeline for litigation from provided source documents, producing a structured chronology table with citations, disputed/undisputed flags, and gap analysis for attorney review.

zgbrenner/agentcounsel · 40 tokens

Claim Chart

Use when building an element-by-element claim chart — mapping patent claim limitations or the elements of a civil cause of action or affirmative defense against evidence — to produce a structured gap analysis for attorney review.

zgbrenner/agentcounsel · 42 tokens