Absorb

/absorb — Session Knowledge Distillation

"What did this session teach us that no file in the repo can?"

Extract project understanding from the current session and persist it to memory. Not code patterns — those live in the code. This captures intent, direction, vision, domain knowledge, and decisions that would otherwise evaporate when context clears.

Memory Location

By default, this skill writes to ~/.claude/memory/. To use a different location, set the CLAUDE_MEMORY_DIR environment variable:

export CLAUDE_MEMORY_DIR="$HOME/my-claude-memory"

Throughout this skill, $MEMORY refers to that directory (${CLAUDE_MEMORY_DIR:-$HOME/.claude/memory}).

When to Use

• End of a deep session where you learned things about a project's purpose or direction
• After domain modeling discussions (data schemas, taxonomies, business rules)
• After architectural decisions that have a why behind them
• When the user shared context about stakeholders, timelines, or vision
• Before /compact or session end to preserve understanding

Arguments

/absorb                    — Full session distillation
/absorb @project:name      — Scope to a specific project
/absorb @dry               — Show what would be saved without writing

Phase 1: NIGREDO — Extract Raw Knowledge

Scan the entire conversation for knowledge that is NOT derivable from code, git history, or existing docs.

1.1 Classify Findings

For each insight, classify into exactly one type:

1.2 Build the Prima Materia

For each finding, capture:

- insight: [one-line statement]
  type: [from table above]
  evidence: [what in the session proves this — quote or reference]
  novelty: [new | extends | contradicts | duplicate]
  weight: [critical | important | useful | noise]

Drop anything classified as noise or duplicate.

Phase 2: ALBEDO — Purify Against Existing Memory

Read the current memory state:

cat $MEMORY/MEMORY.md

Then check each relevant topic file:

# If project-scoped, read the project memory
cat $MEMORY/project_{name}.md 2>/dev/null

For each insight:

Key rule: Real observations from this session beat prior assumptions. If we learned something contradicts an old memory, the new learning wins.

Phase 3: CITRINITAS — Structure for Persistence

3.1 Project Memory Files

For project-scoped insights, organize into a project_{name}.md file with this structure:

---
name: Project Name
description: One-line — what this project is
type: project
---

## Intent
[Why this project exists. The problem it solves. Who it serves.]

## Direction
[Current phase. What's being built now. Near-term priorities.]

## Vision
[Long-term aspiration. What it becomes when "done".]

## Domain Knowledge
[Business concepts, taxonomies, terminology, rules that aren't in the code.]

## Key Decisions
[Architectural choices with WHY. Format: "Decision — because Reason."]

## Stakeholders
[Who's involved, their role, their preferences.]

Only include sections that have content. Don't create empty sections.

3.2 Feedback Files

For workflow preferences, create or update feedback_{topic}.md:

---
name: Feedback topic
description: One-line rule
type: feedback
---

[Rule statement]

**Why:** [reason from session]
**How to apply:** [when/where this kicks in]

3.3 MEMORY.md Index

After creating/updating topic files, update the MEMORY.md index:

• Add one-line pointer for any new file: - [Title](file.md) -- one-line hook
• Keep entries under 150 chars
• Don't duplicate content — the index points, it doesn't store

3.4 Project CLAUDE.md

If insights are project-specific instructions (not observations but directives), consider updating the project's CLAUDE.md instead:

• Terminology rules ("never use X, always say Y")
• Build commands
• Architecture constraints
• Domain-specific coding rules

CLAUDE.md = instructions for Claude. Memory = observations about the world.

Phase 4: RUBEDO — Write and Verify

4.1 Write Files

Use Write/Edit tools to persist each insight to the correct file. Create new topic files when a project doesn't have one yet.

4.2 Coherence Check

After writing:

• No duplicate entries across files
• No secrets or ephemeral data (task IDs, temp paths) in memory
• Each memory file has correct frontmatter (name, description, type)
• MEMORY.md index has pointers to all new files
• Insights are written as durable facts, not session narration
  • Bad: "Today we discovered that the energies table has misclassified entries"
  • Good: "The energies table contains 36 form types — not all are energies. Items with () syntax (eg flight(), Clearing()) are functions/commands, misclassified under form='energy'"

4.3 Potency Report

ABSORBED
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Project: {project name or "cross-project"}

Insights captured:
  + {insight 1} [{type}]
  + {insight 2} [{type}]
  ~ {merged with existing} [{type}]
  - {skipped — duplicate/noise}

Files updated:
  {path}  [{N} changes]
  {path}  [created]

Understanding depth: {shallow | moderate | deep}
  shallow  = facts only, no vision/intent captured
  moderate = intent + direction + some domain knowledge
  deep     = full picture: intent, vision, domain, decisions, stakeholders
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

What NOT to Absorb

• Code patterns, file paths, function signatures — read the code
• Git history, who changed what — use git log
• Debugging solutions — the fix is in the commit
• Anything already in CLAUDE.md files
• Temporary state (current task, in-progress work)
• Speculative conclusions from a single data point

The test: "Would a future session benefit from knowing this, AND can't discover it from the codebase?" If both yes, absorb it.

Integration with Other Skills