# Recommend

Get research-backed architecture advice for your knowledge system.

- Repository: https://github.com/agenticnotetaking/arscontexta (3518 stars)
- Category: Writing
- License: MIT
- Last updated: 2026-02-24
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add agenticnotetaking/arscontexta --skill recommend -g -a claude-code -y`
Codex: `npx skills add agenticnotetaking/arscontexta --skill recommend -g -a codex -y`
Cursor: `npx skills add agenticnotetaking/arscontexta --skill recommend -g -a cursor -y`
Gemini CLI: `npx skills add agenticnotetaking/arscontexta --skill recommend -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add agenticnotetaking/arscontexta`

## Description

Get research-backed architecture advice for your knowledge system. Describe your use case, constraints, and goals, get specific recommendations grounded in TFT research with rationale for each decision. Triggers on "/recommend", "what would you recommend", "architecture advice", "knowledge system for".

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

## Runtime Configuration (Step 0, before any processing)

Read these files to configure recommendation behavior:

1. **`${CLAUDE_PLUGIN_ROOT}/reference/tradition-presets.md`**, tradition and use-case presets
   - Pre-validated coherence points in the 8-dimension space
   - Starting points for customization, not final answers

2. **`${CLAUDE_PLUGIN_ROOT}/reference/methodology.md`**, universal methodology principles

3. **`${CLAUDE_PLUGIN_ROOT}/reference/components.md`**, component blueprints (what can be toggled)

4. **`${CLAUDE_PLUGIN_ROOT}/reference/dimension-claim-map.md`**, maps each dimension position to supporting research claims

5. **`${CLAUDE_PLUGIN_ROOT}/reference/interaction-constraints.md`**, hard blocks, soft warns, cascade effects between dimensions

6. **`${CLAUDE_PLUGIN_ROOT}/reference/claim-map.md`**, topic navigation for the research graph

If any reference file is missing, note the gap but continue with available information. The recommendation degrades gracefully, fewer citations, same structure.

---

## EXECUTE NOW

**Target: $ARGUMENTS**

Parse immediately:
- If target is empty or a question: enter **conversational mode**, ask 1-2 clarifying questions, then recommend
- If target contains a use case description: proceed directly to **recommendation mode**
- If target contains `--compare [A] [B]`: enter **comparison mode**, compare two presets or configurations

**START NOW.** Reference below defines the workflow.

---

## Philosophy

**Advisory, not generative.**

/recommend exists for exploration. The user is considering a knowledge system, maybe they have a use case, maybe they're comparing approaches, maybe they're curious what the research says about a specific pattern. /recommend answers with specific, research-backed reasoning without creating any files.

The rest: https://github.com/agenticnotetaking/arscontexta/blob/HEAD/skills/recommend/SKILL.md