Agent skill

Mediation Problem Generator

by lawve-ai in lawve-ai/awesome-legal-skills

Create original, competition-ready commercial mediation problems and confidential packets with iterative validation.

Apache-2.0Auto-check passedLegal & Compliance

Install Mediation Problem Generator

skills CLI
$ npx skills add lawve-ai/awesome-legal-skills --skill mediation-problem-generator -a claude-code

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

GitHub CLI
$ gh skill install lawve-ai/awesome-legal-skills mediation-problem-generator --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/mediation-problem-generator-seth-chandler .claude/skills/mediation-problem-generator && 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
mediation-problem-generator
GitHub stars
842
Token cost
~3.5k tokens
SKILL.md length
1,666 words
Files
11 (incl. scripts)
Skills in repo
154
Repo updated
First seen
Licence
Apache-2.0

At a glance

Create original, competition-ready commercial mediation problems and confidential packets with iterative validation.

  • Works in 6 steps: case-model.json - author-only; never… → general-information.md - available to… → confidential-information-party-a.md. → …
  • A user provides a topic
  • SKILL.md covers Load the Required Guidance, Select the Entry Route, Build the Canonical Model First and Design a Narrow but Sound…, plus 8 more sections
  • Runs Python scripts from its folder; calls python3

What it does

Mediation Problem Generator is an agent skill from lawve-ai/awesome-legal-skills. Create original, competition-ready commercial mediation problems and confidential packets with iterative validation. Use when a user provides a topic, industry, dispute sketch, or existing general-information packet and wants a public packet plus confidential packets for both sides—or one named side. Build a narrow but workable settlement corridor; verify factual and numerical consistency, information asymmetry, balance, originality, and commercial feasibility; and revise until deterministic and semantic exit…

Its SKILL.md is about 3.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 12 other files, including scripts (for example `README.md`, `resources/case-model-schema.md` and `resources/design-grammar.md`).

It sits in Legal & Compliance, covering Dispute resolution. It works with Python. 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 user provides a topic
  • Existing general-information packet and wants a public packet plus confidential packets for both sides—or one named side

Example prompts

  • “/mediation-problem-generator”

Requirements

  • Python 3

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. case-model.json - author-only; never distribute to participants.
  2. general-information.md - available to both parties.
  3. confidential-information-party-a.md.
  4. confidential-information-party-b.md.
  5. validation-report.md - author-only.
  6. clarification-risk.md - author-only.

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

    Ships 3 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python3

    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

Mediation Problem Generator loads about 3.5k tokens when it runs. Until then it costs about 196 tokens; SKILL.md has 1,666 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~196
When it runs · the whole SKILL.md, loaded when a task matches
~3.5k

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); the scripts in this folder 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). 1,666 words, ~3,487 tokens.

Download SKILL.mdSave it as .claude/skills/mediation-problem-generator/SKILL.md (or your agent's skills folder). This skill also uses 10 other files; get the full folder from GitHub.
name
mediation-problem-generator
description
Create original, competition-ready commercial mediation problems and confidential packets with iterative validation. Use when a user provides a topic, industry, dispute sketch, or existing general-information packet and wants a public packet plus confidential packets for both sides—or one named side. Build a narrow but workable settlement corridor; verify factual and numerical consistency, information asymmetry, balance, originality, and commercial feasibility; and revise until deterministic and semantic exit criteria pass. Do not use merely to summarize an existing packet or to advise parties in a real dispute. Requires local file access; Python 3 is recommended for bundled deterministic checks, with disclosed manual fallbacks when unavailable.
metadata.author
Seth J. Chandler
metadata.author_link
https://legaled.ai
metadata.license
Apache-2.0
metadata.version
2026-08-07
metadata.jurisdiction
All
metadata.language
English
metadata.category
legal-education
metadata.requires
Local file access; Python 3 recommended

Mediation Problem Generator

Create original, competition-ready commercial mediation materials. Treat internal consistency, balanced difficulty, and a narrow but workable settlement corridor as design requirements rather than cleanup tasks.

Load the Required Guidance

Read all four references before drafting:

  • resources/case-model-schema.md for the author-only source of truth.
  • resources/design-grammar.md for problem construction and originality rules.
  • resources/packet-templates.md for the public and confidential packet structures.
  • resources/semantic-audit.md for balance, feasibility, and exit criteria.

Before promising outputs, confirm that the host can read and write local files. Python 3 is recommended for the bundled deterministic checks. If Python is unavailable, perform the manual fallbacks described below and state in the delivery summary which scripts were not run.

Select the Entry Route

Route A - Sparse Prompt to Full Package

Use when the user supplies a topic area, industry, relationship, dispute seed, or short sketch.

Produce by default:

  1. case-model.json - author-only; never distribute to participants.
  2. general-information.md - available to both parties.
  3. confidential-information-party-a.md.
  4. confidential-information-party-b.md.
  5. validation-report.md - author-only.
  6. clarification-risk.md - author-only.

Make reasonable creative assumptions. Ask a question only when a missing choice would materially change the exercise and guessing would create a substantial risk of divergence. Otherwise state the assumptions in the author-only model and continue.

Route B - General Packet to Confidential Packets

Use when the user provides a general packet in PDF, DOCX, Markdown, or text.

  1. Extract and inspect the complete packet using whatever document-reading capability the host provides. If the host cannot reliably read the format, ask the user for extracted text or a supported conversion; do not claim to have inspected content that was unavailable.
  2. Reconstruct all public facts in case-model.json without changing them.
  3. Design the hidden settlement architecture for both sides together.
  4. Generate both confidential packets by default.
  5. If the user requests one named side only, deliver only that packet, but still design both sides' private constraints and the full settlement corridor in the author-only model. Do not generate or expose the unrequested packet.

Never repair, contradict, or silently supplement a supplied public fact in a distributed packet. Record defects or necessary assumptions in validation-report.md and, if material, ask the user before finalizing.

Build the Canonical Model First

Never draft the distributed packets independently. Create case-model.json first and record:

  • objective public facts and chronology;
  • party identities, roles, authority, and relationships;
  • claims, defenses, and deliberately unresolved legal questions;
  • financial data and calculation rules;
  • each side's positions, interests, constraints, targets, reservation conditions, BATNA, and WATNA;
  • fact visibility and epistemic status;
  • protected interests that cannot simply be traded away;
  • cross-trades, contingent terms, implementation mechanisms, and candidate packages;
  • the intended settlement corridor and its failure boundaries.

Classify every material fact as objective, belief, allegation, legal_uncertainty, or deliberate_ambiguity. Classify visibility as public, party:<party-id>, shared_private, or author_only.

Use <skill-dir>/scripts/scaffold_case_model.py to create a starting model when useful. Resolve <skill-dir> to this skill's directory. Validate the model with <skill-dir>/scripts/validate_case_model.py after every material revision.

Design a Narrow but Sound Settlement Corridor

Require all of the following:

  • At least two and ordinarily no more than four materially different sound packages.
  • No sound package that merely splits the public monetary positions without using confidential information.
  • At least two linked concessions in each sound package.
  • At least one value-creating, non-cash, contingent, relational, informational, or implementation term.
  • A credible reason each party prefers settlement to its BATNA.
  • A protected interest or hard constraint for each party.
  • Enough overlap for agreement, but not enough for an obvious or costless agreement.
  • No package that requires a party to promise money, authority, rights, performance, or information it does not possess.

Reject designs that are impossible, depend on one brittle hidden solution, make one side dominant on every dimension, or reveal the complete bargain merely by reading either confidential packet.

Draft the Packets

Generate the public packet only from public fields in the model. Provide enough commercial, legal, financial, and relational context to make the dispute understandable without disclosing reservation values or intended trades.

Generate each confidential packet only from:

  • the public model;
  • that party's private facts;
  • facts the party could reasonably know;
  • its beliefs and allegations clearly labeled as such.

Write each packet in second person unless the user requests another convention. Give each side realistic internal tensions, priorities, and authority. Do not tell a party the other side's secret or prescribe a single settlement script.

Do not give both packets parallel menus of the same candidate packages. If one party has internally considered a direction, describe only that party's partial concept and the dependencies it cannot resolve alone. Present tradeable ingredients and constraints asymmetrically; leave package assembly to the mediation.

Follow resources/packet-templates.md. Preserve a supplied packet's style and naming conventions when using Route B.

Run the Iterative Validation Loop

Repeat this cycle:

  1. Validate case-model.json with:

    python3 <skill-dir>/scripts/validate_case_model.py <case-model.json>

  2. Run the information-firewall check after drafting:

    python3 <skill-dir>/scripts/check_information_firewall.py <case-model.json> <general.md> --party-a <party-a.md> --party-b <party-b.md>

    When Route B produces one side only, supply only the corresponding --party-a or --party-b option.

  3. Apply every semantic audit in resources/semantic-audit.md.

  4. Record defects by severity in validation-report.md.

  5. Revise the canonical model, not an isolated packet.

  6. Regenerate every affected packet.

  7. Repeat until the exit criteria pass.

Treat deterministic scripts as minimum checks. They do not replace semantic review.

Manual fallback when Python is unavailable

Before delivery, manually verify the required top-level model fields, exactly two parties, visibility and epistemic-status labels, required private-case fields, two to four candidate packages, calculations and payment totals, the narrow-window settings, and the last two audit iterations. Compare each distributed packet against the model's visibility labels for possible leaks. Record that the manual fallback was used; never describe it as equivalent to running the scripts.

Show full SKILL.md (733 more words)Show less

Use Information-Firewall Simulations

When independent agents are available, run role-limited audits:

  • Party A auditor: general packet plus Party A packet only.
  • Party B auditor: general packet plus Party B packet only.
  • Mediator auditor: general packet only.
  • Full-package auditor: case model and all packets.

Instruct role-limited auditors not to inspect the workspace or any unprovided artifact. If true file isolation is unavailable, pass only the permitted text and treat the exercise as an independence aid, not a security boundary.

Ask each side auditor to identify interests, constraints, likely proposals, apparent BATNA, confusing facts, and at least two sound settlement packages. Ask the mediator auditor whether the public problem supports productive negotiation without disclosing the answer. Ask the full-package auditor to test feasibility, balance, leaks, and contradictions.

If independent agents are unavailable, perform the same audits sequentially with fresh notes and strict information partitions.

Enforce the Exit Criteria

Do not call the package final until:

  • all deterministic errors are cleared;
  • all high-severity semantic defects are cleared;
  • the last two audit iterations introduce no new high-severity defect;
  • each side-limited audit finds at least two plausible packages;
  • the full audit confirms two to four materially different sound packages;
  • no private fact leaks into the public packet or the opposing packet;
  • all payments, valuations, ownership interests, dates, and authorities reconcile;
  • likely clarification questions have answers or are intentionally designated as unresolved legal or factual ambiguities;
  • the originality check finds no copied scenario, wording, distinctive combination, or numerical pattern from an example source.

Run the final deterministic check with:

python3 <skill-dir>/scripts/validate_case_model.py <case-model.json> --final

If five revision cycles do not satisfy the criteria, stop and report the remaining defects and the design choice needed. Do not conceal failure by weakening the rubric.

Deliver Safely

Keep author-only artifacts separate from participant packets. Clearly label confidential packets and their intended recipient. Never combine both confidential packets in a participant-facing file.

Deliver Markdown by default. Create DOCX or PDF versions only when requested and when the host provides a document-generation capability with visual verification. Otherwise deliver Markdown and state that the requested conversion could not be completed in the current host.

Summarize:

  • the selected entry route;
  • the files created;
  • the number of validation cycles;
  • whether all exit criteria passed;
  • any unresolved author judgment calls.

Use the model, validation report, and audit history to preserve continuity across revision cycles.

Jurisdiction and professional use

This skill is jurisdiction-neutral because it designs fictional teaching simulations rather than resolving substantive law. When a problem depends on actual doctrine, procedure, ethics rules, or enforceability, the user must supply authoritative jurisdiction-specific sources or independently verify the legal framework before distribution. The generated materials are educational exercises, not legal advice or predictions about a real dispute.

Bundled resources

  • resources/case-model-schema.md — canonical author-only model; read before constructing a case.
  • resources/design-grammar.md — originality, hidden-value, difficulty, and commercial-soundness rules; read before designing the settlement corridor.
  • resources/packet-templates.md — distributed and author-only document structures; read before drafting packets or reports.
  • resources/semantic-audit.md — severity rubric and exit criteria; use during every revision.
  • scripts/scaffold_case_model.py — optional Python 3 utility that writes a starter JSON model to the caller-named path and refuses to overwrite unless expressly told to do so.
  • scripts/validate_case_model.py — Python 3 deterministic validator; it reads a model and writes a report only when the caller supplies a report path.
  • scripts/check_information_firewall.py — read-only Python 3 comparison for likely verbatim confidential-fact leakage.

Limitations and risks

  • The skill cannot establish that invented law, contractual language, industry practice, or financial assumptions are accurate without authoritative sources and human review.
  • Deterministic validation catches structural and arithmetic defects, not every semantic leak, impractical bargain, unfair role, or pedagogical weakness. Role-limited audits remain judgment aids, and simulated agent separation is not a security boundary.
  • Author-only models and opposing confidential packets can compromise an exercise if distributed to participants. Keep them separate and verify each delivery target.
  • Do not place privileged, confidential, personal, or client information into an AI host unless authorized and consistent with the host's privacy, retention, and security terms.
  • The output is a teaching simulation, not legal advice, a settlement recommendation, or a substitute for review by a qualified instructor or lawyer in the relevant jurisdiction.

The package contains three Python 3 scripts using only the standard library. They make no network calls, spawn no subprocesses, access no credentials, and evaluate no dynamic code. The scaffold writes only to the caller-named path; the validator writes only to an optional caller-named report path; the firewall checker is read-only.

© 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 10 other files (scripts) in skills/mediation-problem-generator-seth-chandler of lawve-ai/awesome-legal-skills.

  • SKILL.md
  • LICENSE
  • NOTICE
  • README.md
  • resources/case-model-schema.md
  • resources/design-grammar.md
  • resources/packet-templates.md
  • resources/semantic-audit.md
  • scripts/check_information_firewall.py
  • scripts/scaffold_case_model.py
  • scripts/validate_case_model.py

Open the folder on GitHubat commit 045f738

Compare with similar skills

Mediation Problem Generator 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.

Mediation Problem Generator compared with similar skills
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Moot Court Simulation Buildercat-xierluo/legal-skills717—~1.4kAutomated safety check: PassCC-BY-NC-4.0
Alkahest Developerinternet-court/internet-court-skill6.5k1 repos~2.3kAutomated safety check: PassMIT
Hand Drawnthreerocks/hand-drawn-styles2.2k—~398Automated safety check: PassMIT
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Tw Legal RAGaa0101181514/tw-legal-rag328—~580Automated safety check: PassCustom licence

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Works with

Questions about Mediation Problem Generator

What does Mediation Problem Generator do?

Create original, competition-ready commercial mediation problems and confidential packets with iterative validation. Mediation Problem Generator is an agent skill from lawve-ai/awesome-legal-skills. Create original, competition-ready commercial mediation problems and confidential packets with iterative validation.

When should I use Mediation Problem Generator?

Mediation Problem Generator fits situations like: A user provides a topic; existing general-information packet and wants a public packet plus confidential packets for both sides—or one named side.

How do I install Mediation Problem Generator in Claude Code?

Run `npx skills add lawve-ai/awesome-legal-skills --skill mediation-problem-generator -a claude-code`. Or copy the skill folder (skills/mediation-problem-generator-seth-chandler in lawve-ai/awesome-legal-skills) into .claude/skills/mediation-problem-generator in your project. Claude Code loads it when a task matches its description.

How do I install Mediation Problem Generator in Codex?

Run `npx skills add lawve-ai/awesome-legal-skills --skill mediation-problem-generator -a codex`. Or copy the skill folder (skills/mediation-problem-generator-seth-chandler in lawve-ai/awesome-legal-skills) into .agents/skills/mediation-problem-generator in your project. Codex loads it when a task matches its description.

Can I use Mediation Problem Generator 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 mediation-problem-generator -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/mediation-problem-generator, .gemini/skills/mediation-problem-generator, .github/skills/mediation-problem-generator and .opencode/skills/mediation-problem-generator in your project.

What does Mediation Problem Generator need to run?

Going by SKILL.md and its folder, Mediation Problem Generator needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3.

Does Mediation Problem Generator 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 Mediation Problem Generator 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Mediation Problem Generator use?

Mediation Problem Generator 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 Mediation Problem Generator use?

About 3.5k tokens (SKILL.md is roughly 14k 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 Mediation Problem Generator?

Skills that share tags, products or a category with Mediation Problem Generator: Moot Court Simulation Builder (cat-xierluo/legal-skills, 717 stars), Alkahest Developer (internet-court/internet-court-skill, 6.5k stars), Hand Drawn (threerocks/hand-drawn-styles, 2.2k stars) and HIPAA Safe Harbor Coverage Audit (maziyarpanahi/openmed, 5.5k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Mediation Problem Generator?

lawve-ai (a GitHub organization) maintains it in lawve-ai/awesome-legal-skills, which has 842 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.