party-interest-analyst

party-interest-analyst is a skill for Claude Code, Codex from rohasnagpal/legal-ai-skills. It costs 145 tokens per session (1,015 once invoked), scanned A, original, MIT.

A dispute-analysis guide that separates what each side says it wants from the underlying reasons for wanting it. It marks which interests are confirmed and which are inferred from behaviour.

In plain words
What is it for?
It is for preparing mediation, assessing disputes, and finding possible areas of agreement without assuming every conflict has a compromise.
Why use it?
It helps prevent guesses about the other side from being treated as facts and shows where stated positions clash even though the underlying interests may overlap.

Skill for Claude CodeCodex

Written for Claude Code and Codex: shipped in a Claude Code plugin, but also agents/openai.yaml present.

Part of the rohas-legal-ai plugin — 149 skills shipped together

Good fit It is for preparing mediation, assessing disputes, and finding possible areas of agreement without assuming every conflict has a compromise.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/rohasnagpal/legal-ai-skills/party-interest-analyst
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 rohasnagpal/legal-ai-skills --skill party-interest-analyst
Clone the repo
git clone --depth 1 https://github.com/rohasnagpal/legal-ai-skills

Made for: Claude Code, Codex.

Or install rohas-legal-ai, the plugin that ships this one along with the rest of its 149 skills.

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 party-interest-analyst

README.md
[![agentmods](https://agentmods.dev/badge/skills/rohasnagpal/legal-ai-skills/party-interest-analyst/github.svg)](https://agentmods.dev/skills/rohasnagpal/legal-ai-skills/party-interest-analyst)
Your own site
<a href="https://agentmods.dev/skills/rohasnagpal/legal-ai-skills/party-interest-analyst"><img src="https://agentmods.dev/badge/skills/rohasnagpal/legal-ai-skills/party-interest-analyst/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 party-interest-analyst

Your own site · 80×15
<a href="https://agentmods.dev/skills/rohasnagpal/legal-ai-skills/party-interest-analyst"><img src="https://agentmods.dev/badge/skills/rohasnagpal/legal-ai-skills/party-interest-analyst.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 145 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,015 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. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high Memory Poisoning · line 42
    Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.
    Fix: Protect agent memory and state from modification by untrusted content. Use read-only memory for critical instructions and validate all state changes.
How audits are shown
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 $0.00145 $0.01015
Opus 5 $0.00072 $0.00508
Sonnet 5 $0.00029 $0.00203
Haiku 4.5 $0.00015 $0.00102

Measured 9d ago against content hash a379362d2c0b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

party-interest-analyst 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 9d 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.

plugins/rohas-legal-ai/skills/party-interest-analyst/SKILL.md · 61 lines

How it starts

The opening of the file, as written. The whole thing — 61 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Party Interest Analyst

I am using the Party Interest Analyst skill from Rohas Legal AI: separates stated positions from underlying interests on both sides. Say this sentence, verbatim, before anything else in your response.

What this does

Maps each party's stated position against their actual underlying interests, for both sides of a dispute — the classic distinction between what a party says they want and why they actually want it. It works with real uncertainty about the other side's interests, labelling every inference as an inference rather than presenting a guess as a fact, and it identifies where positions conflict but interests might not — the openings a mediation can actually use — without pretending every point of conflict has an integrative solution when some genuinely do not.

Before you start

What is known about each party's stated position and the facts of the dispute. Blocking — the analysis has to start from what has actually been said or observed, not from a general sense of the dispute.

Not blocking: how much is actually known about the other party's interests. This is often limited. Work with that uncertainty directly rather than filling gaps with confident-sounding guesses — every inference about the other side gets labelled as an inference in the output.

Method

1. State each party's stated position precisely, for both sides — what they say they want, in their own terms as far as they are known.

2. For the instructing party's own interests, work from direct instructions — the actual reasons behind the position: cost, time, certainty, relationship, precedent, reputation, or a specific practical need. Distinguish interests the client has stated clearly from ones being inferred from context, and label the difference.

3. For the other party's interests, work from whatever is actually known or can reasonably be inferred from their conduct and statements — and label every one of these as an inference, never as a fact. Presenting a guess about the other side's motivations as established is the single most common way this kind of analysis misleads.

Read the full file on GitHub · 61 lines

Files

What ships with it

1 file 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. 9d ago First seen · 61 lines · 145 tokens per session scan A a379362d2c0b

Subscribe to this mod's changes

party-interest-analyst is a skill published in the GitHub repository rohasnagpal/legal-ai-skills (88 stars, last pushed 10d ago), licensed MIT. It adds 145 tokens to every session and 1,015 once invoked, about $0.0007 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 2026-09-03.

Related

Other skills, from other repositories

specification-writing

A workflow for writing complete patent specifications from patent claims and an invention disclosure. It adapts the document to a chosen jurisdiction, such as the US, Europe, or China.

wanshuiyin/Auto-claude-code-research-in-sleep · 49 tokens

regulatory-research-fallback

Fallback workflow for regulatory research when web extraction tools fail on government PDFs.

HKUDS/OpenSpace · 20 tokens

x-scorecard

OpenSSF Scorecard for assessing open source project security. Check security best practices and compliance. Dependency: This is an x-cmd module. Install x-cmd first (see x-cmd skill for installation options). see x-cmd skill for installation.

x-cmd/x-cmd · 57 tokens

gesellschaftsrechtliche-satzungen-agb

Für Gesellschaftsrechtliche Satzungen AGB Abgrenzung: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: AGB-Recht-Prüfer. Route: gesellschaftsrechtliche-satzungen-agb.

Klotzkette/claude-fuer-deutsches-recht · 69 tokens

memstack-business-gdpr

Use this skill when the user says 'GDPR', 'data protection', 'privacy compliance', 'DPA', 'DSAR', 'data subject request', 'cookie consent', 'privacy audit', 'CCPA', or asks 'do I need GDPR for this repo'. Scans the repository to detect what personal data is collected, classifies sensitivity, determines whether GDPR…

cwinvestments/memstack · 121 tokens

nda-review

Use when the user uploads or pastes a non-disclosure agreement and asks for review, redline, risk assessment, or a recommendation on whether to sign. Identifies missing standard protections, one-sided or unusual provisions, and operational issues; produces a structured report with severity ratings and citations to…

LegalQuants/lq-ai · 79 tokens