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/memory-audit

Show everything Claudia knows with provenance tracing and entity counts. Triggers on "what do you know?", "show memories", "memory audit", "what do you remember about". See also: `memory-health` for system-level stats and data quality; `diagnose` for connectivity troubleshooting.

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claudia
28333 skills6 agents
Install
$ npx -y skills add kbanc85/claudia --skill memory-audit --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/memory-audit

Context preview

The summary Claude sees to decide when to auto-load this skill.

Show everything Claudia knows with provenance tracing and entity counts. Triggers on "what do you know?", "show memories", "memory audit", "what do you remember about". See also: `memory-health` for system-level stats and data quality; `diagnose` for connectivity troubleshooting.

SKILL.md

memory-audit.SKILL.md
name: memory-audit
description: Show everything Claudia knows with provenance tracing and entity counts. Triggers on "what do you know?", "show memories", "memory audit", "what do you remember about". See also: `memory-health` for system-level stats and data quality; `diagnose` for connectivity troubleshooting.
argument-hint: "[entity name]"
effort-level: medium

Memory Audit

Show what Claudia knows. Verify claims trace to sources. Surface gaps.

Usage

  • `/memory-audit` -- Full system audit
  • `/memory-audit [entity name]` -- Audit everything about a specific person, project, or entity

Full Audit

When run without arguments, produce a system-level overview of everything in memory.

1. Summary Counts

Query the memory system for aggregate counts:

claudia memory entities search --query "*" --project-dir "$PWD"
claudia memory recall "*" --compact --limit 1 --project-dir "$PWD"
claudia memory document search --project-dir "$PWD"

Parse the JSON output from each command to get counts.

Display:

## Memory Audit - [Date]

| Category       | Count |
|----------------|-------|
| Entities       | N     |
| Memories       | N     |
| Commitments    | N     |
| Documents      | N     |
| Relationships  | N     |

2. People (Top 10 by Importance)

claudia memory entities search --types "person" --limit 10 --project-dir "$PWD"
For each person:
  claudia memory about "[person name]" --project-dir "$PWD"

Display as a table:

### People

| Name | Memories | Last Mentioned | Key Fact |
|------|----------|----------------|----------|
| ...  | ...      | ...            | ...      |

3. Projects (Top 10)

Same pattern with types=["project"]:

claudia memory entities search --types "project" --limit 10 --project-dir "$PWD"

4. Active Patterns

claudia memory session context --project-dir "$PWD"

5. Provenance Sample

Pick the 3 most recent high-importance memories and trace them:

claudia memory recall "*" --compact --limit 3 --project-dir "$PWD"
For each result, run:
  claudia memory provenance trace --memory-id "[id]" --project-dir "$PWD"

Display:

### Provenance Check (3 recent memories)

**Memory:** "[content snippet]"
- Source: [episode/document/user_input]
- Document: [filename] (if linked)
- Entities: [linked entities]
- Verified: [yes/no/pending]

---

Entity Audit

When run with an entity name (e.g., `/memory-audit Sarah Chen`):

1. Profile

claudia memory about "[entity name]" --project-dir "$PWD"

Display:

## Audit: [Entity Name]

**Type:** person/project/organization
**Description:** [from entity record]
**Importance:** [score]
**First seen:** [created_at]
**Last mentioned:** [updated_at]

2. All Memories (grouped by type)

From the `claudia memory about` JSON response, group memories:

### Facts (N)
- [content] (importance: X, created: date)

### Commitments (N)
- [content] (importance: X, created: date)

### Observations (N)
- [content] (importance: X, created: date)

3. Relationships

### Relationships (N)
- [relationship_type] with [other_entity] (strength: X)

4. Linked Documents

claudia memory document search --entity "[entity name]" --project-dir "$PWD"

Display:

### Documents (N)
- [filename] ([source_type], [date]) - [summary snippet]

5. Provenance Chains

For each commitment or high-importance memory (importance > 0.7):

claudia memory provenance trace --memory-id "[memory ID]" --project-dir "$PWD"

Display:

### Provenance

**"[memory content]"** (commitment, importance: 0.9)
|- Source: session_summary (episode 42)
|- Episode: "Discussed Q2 goals with Sarah..."
|- Document: meeting-sarah-q2.md (transcript)
|- Verified: yes (2026-01-15)

---

Output Rules

  • Use the structured output format with emoji headers
  • End structured output blocks with a markdown horizontal rule
  • If the memory system is not available, say so clearly
  • Keep entity audit focused: no padding, no speculation
  • Provenance chains are the most important part: if a memory has no source, flag it

Tone

  • Factual and clean
  • Like a database report, not a narrative
  • Flag gaps honestly: "No source document linked" is useful information
Read more
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Terminal-based AI chief of staff. Remembers relationships, tracks commitments, helps you think strategically. Runs on Claude Code.

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