/knowledge-intake

name: knowledge-intake
description: Processes external resources into stored knowledge with quality scoring and routing. Use when ingesting articles, papers, or docs into a memory palace.
alwaysApply: false
category: governance
tags:
- knowledge-management
- intake
- evaluation
- curation
- external-resources
dependencies:
- memory-palace-architect
- digital-garden-cultivator
- leyline:evaluation-framework
- leyline:storage-templates
- leyline:document-conversion
- scribe:slop-detector
scripts: []
usage_patterns:
- resource-intake
- knowledge-evaluation
- application-routing
complexity: intermediate
model_hint: standard
estimated_tokens: 950

Table of Contents

• [What It Is](#what-it-is)
• [The Intake Signal](#the-intake-signal)
• [Quick Start](#quick-start)
• [Evaluation Framework](#evaluation-framework)
• [Importance Criteria](#importance-criteria)
• [Scoring Guide](#scoring-guide)
• [Application Routing](#application-routing)
• [Local Codebase Application](#local-codebase-application)
• [Meta-Infrastructure Application](#meta-infrastructure-application)
• [Routing Decision Tree](#routing-decision-tree)
• [Storage Locations](#storage-locations)
• [The Tidying Imperative (KonMari-Inspired)](#the-tidying-imperative-konmari-inspired)
• [The Master Curator](#the-master-curator)
• [The Two Questions](#the-two-questions)
• [Tidying Actions](#tidying-actions)
• [Marginal Value Filtering (Anti-Pollution)](#marginal-value-filtering-anti-pollution)
• [The Three-Step Filter](#the-three-step-filter)
• [Using the Filter](#using-the-filter)
• [Filter Output Example](#filter-output-example)
• [Progressive Autonomy Integration](#progressive-autonomy-integration)
• [RL-Based Quality Scoring](#rl-based-quality-scoring)
• [Anchor-Question Clarity Gate](#anchor-question-clarity-gate)
• [Usage Signals](#usage-signals)
• [Quality Decay Model](#quality-decay-model)
• [Source Lineage Tracking](#source-lineage-tracking)
• [Knowledge Orchestrator](#knowledge-orchestrator)
• [RL Integration with Marginal Value Filter](#rl-integration-with-marginal-value-filter)
• [Workflow Example](#workflow-example)
• [Queue Processing](#queue-processing)
• [Processing Queue Entries](#processing-queue-entries)
• [Queue Integration](#queue-integration)
• [Queue Status Workflow](#queue-status-workflow)
• [Automation](#automation)
• [Detailed Resources](#detailed-resources)
• [Hook Integration](#hook-integration)
• [Automatic Triggers](#automatic-triggers)
• [Hook Signals](#hook-signals)
• [Deduplication](#deduplication)
• [Safety Checks](#safety-checks)
• [Index Schema Alignment](#index-schema-alignment)
• [Integration](#integration)
• [Exit Criteria](#exit-criteria)

Knowledge Intake

Process external resources into the knowledge store. When a user links an article, blog post, or paper, this skill guides evaluation, storage decisions, and application routing.

When To Use

• Capturing and organizing knowledge from sessions
• Ingesting information into structured memory palaces

When NOT To Use

• Temporary notes that do not need long-term storage
• Code-only changes without knowledge capture needs

What It Is

A knowledge governance framework that answers three questions for every external resource: 1. **Is it worth storing?** - Evaluate signal-to-noise and relevance 2. **Where does it apply?** - Route to local codebase or meta-infrastructure 3. **What does it displace?** - Identify outdated knowledge to prune

The Intake Signal

> When a user links an external resource, it is a signal of importance.

The act of sharing indicates the resource passed the user's own filter. Our job is to:

• Extract the essential patterns and insights
• Determine appropriate storage location and format
• Connect to existing knowledge structures
• Identify application opportunities

Quick Start

When a user shares a link:

1. FETCH    → Detect format, retrieve and convert content
2. EVALUATE → Apply importance criteria
3. DECIDE   → Storage location and application type
4. STORE    → Create structured knowledge entry
5. VALIDATE → Scribe verification (slop scan + doc verify)
6. CONNECT  → Link to existing palace structures
7. PROMOTE  → Offer Discussion promotion (score 80+)
8. APPLY    → Route to codebase or infrastructure updates
9. PRUNE    → Identify displaced/outdated knowledge

Step 1: FETCH with Format Detection

Before retrieving content, detect the source format from the URL or file path to choose the right retrieval method.

**Web articles and blog posts** (default path): Use WebFetch to retrieve HTML content directly. No conversion needed.

**Document URLs** (PDF, DOCX, PPTX, XLSX): Apply the `leyline:document-conversion` protocol. This tries the markitdown MCP tool first for high-quality markdown, then falls back to native Claude Code tools (Read for PDFs, etc.), then informs the user if the format is unsupported without markitdown.

**Local files** (user shares a file path): Construct a `file://` URI from the absolute path and apply the `leyline:document-conversion` protocol.

**Format detection heuristics:**

| URL Pattern | Format | Retrieval | |-------------|--------|-----------| | `*.pdf`, `arxiv.org/pdf/*` | PDF | document-conversion | | `*.docx`, `*.doc` | Word | document-conversion | | `*.pptx`, `*.ppt` | PowerPoint | document-conversion | | `*.xlsx`, `*.xls` | Excel | document-conversion | | `*.epub` | E-book | document-conversion | | `drive.google.com/*` | Various | document-conversion | | Everything else | HTML/web | WebFetch (existing) |

After retrieval (regardless of method), wrap the content in external content boundary markers per `leyline:content-sanitization` before proceeding to Step 2 (EVALUATE).

Step 5: Scribe Validation (Required)

**All knowledge corpus entries MUST pass scribe validation before finalizing.**

Run `Skill(scribe:slop-detector)` on the new entry:

• Score must be < 2.5 (Clean to Light)
• No Tier 1 markers (delve, tapestry, comprehensive, leveraging, etc.)