academy-prompt-library-recommender

Category: General Risk: Unknown ★ 3.9 · Rating 3.9/5 (8) sboghossian/mini-claude-for-legal MIT

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name: academy-prompt-library-recommender
description: Use when a user needs help discovering which prompts in the 152-prompt library are most relevant to their role, jurisdiction, and recent work. Produces personalized prompt recommendations with progressive disclosure (3–5 at a time), and learns from user engagement signals to improve future recommendations. Triggers on "what should I try?", "show me useful prompts", or when a user profile indicates a gap between their stated role and their actual usage patterns.
license: MIT
metadata:
id: academy.prompt-library-recommender
category: academy
jurisdictions: [multi]
priority: P3
intent: [customer-facing, discovery, prompts, personalization]
related: [academy-use-case-explainer, academy-feature-explainer, academy-legal-ai-skills-catalog, academy-solutions-by-persona]
source: Louis — HAQQ Legal AI (github.com/sboghossian/mini-claude-for-legal)
version: "1.0"

Prompt Library Recommender — Personalized Prompt Discovery

When to use this

Invoke when:

  • A new user asks "where do I start?" or "what should I try first?"
  • A returning user asks "what prompts are useful for [practice area]?"
  • A user's usage profile shows they are only using a fraction of relevant capabilities
  • A user selects a role or jurisdiction during onboarding and needs a contextual starting pack
  • An in-product empty state needs to surface relevant entry points

What the Prompt Library is

The Louis Prompt Library contains 152 curated prompts — pre-written starting points for common legal tasks. These are not templates that substitute for skill judgment; they are well-formed entry points that help users:

  • Understand how to phrase requests to get better outputs
  • Discover capabilities they did not know existed
  • Build their own prompt habits faster by starting from proven examples

Prompts are organized by category, practice area, jurisdiction, and role.

Recommendation algorithm — how it works

Inputs

Input Source Weight
User role Profile / onboarding High
Primary jurisdictions Profile / onboarding High
Recent activity Session history (anonymized) Medium
Practice areas worked in Inferred from recent docs / skills used Medium
Prompts already used Usage log Excludes already-used from recommendations
Explicit "not useful" signals User dismiss / thumbs-down Excludes category

Logic

  1. Filter by jurisdiction: surface only prompts relevant to the user's stated jurisdictions. A Beirut lawyer does not need KSA-specific prompts as a priority.
  2. Filter by role: a paralegal and a senior partner have different entry points.
  3. Surface by practice area: if the user has been working on employment matters this week, prioritize employment-adjacent prompts.
  4. Progressive disclosure: show 3–5 prompts, not 50. The goal is actionable discovery, not an overwhelming catalog.
  5. Learn and adjust: if a user clicks and runs a prompt, note the category as high-interest. If a user dismisses repeatedly, reduce that category's frequency.

Recommendation output format

Each recommendation surfaces:

  1. Prompt title (e.g., "Review a UAE employment contract for mandatory clause gaps")
  2. One-sentence description (what it does and when to use it)
  3. Practice area and jurisdiction tags
  4. "Try it" button that pre-fills the prompt into the chat input
  5. Related prompts (1–2 links to similar prompts the user might also want)

Prompt packs by role — defaults

BigLaw / Large-Firm Associate

  • Draft an NDA (jurisdiction-selectable)
  • Review a services agreement for risk (jurisdiction-selectable)
  • Summarize a contract in plain language for a client briefing
  • Flag missing standard clauses in a draft SPA
  • Generate a redline comparison summary

In-House Counsel

  • Review a vendor contract against standard in-house positions
  • Generate a contract register entry from an uploaded agreement
  • Summarize key obligations and renewal dates from a services contract
  • Draft an employment offer letter (jurisdiction-selectable)
  • Identify regulatory compliance obligations in a new market

Solo Practitioner

  • Draft a standard retainer / engagement letter
  • Explain a legal provision in plain language (for client)
  • Summarize what a court judgment means in practical terms
  • Draft a simple services agreement for a client

Law Student / Bar Candidate

  • Generate a case brief in IRAC format
  • Explain a legal principle with examples
  • Quiz me on [subject area] at [difficulty level]
  • Draft a sample exam answer for [fact pattern]
  • Build a study plan for bar exam preparation

Paralegal

  • Extract key dates, parties, and obligations from a contract
  • Summarize a document for file management
  • Check a draft for formatting and cross-reference consistency
  • Generate a document checklist for a closing

Quality standards for prompt recommendations

  • Relevance over completeness. Three relevant prompts are more valuable than 15 marginally relevant ones.
  • Don't re-recommend. Once a user has run a prompt, replace it with the next-best option in that category.
  • Explain the recommendation. A brief "because you recently worked on employment matters in UAE" anchors the recommendation in the user's context and builds trust.
  • Not prescriptive. Recommendations are suggestions. The user sets direction; the recommender surfaces options.

Edge cases

  • New user with no history: default to the role-based starter pack. Prompt for role during onboarding if not set.
  • User with highly varied practice: rotate recommendations across practice areas rather than locking to a single area.
  • User who dismisses everything: surface a "help me find what I need" prompt that asks the user directly what they want to accomplish.
  • [[academy-use-case-explainer]]
  • [[academy-feature-explainer]]
  • [[academy-legal-ai-skills-catalog]]
  • [[academy-solutions-by-persona]]