/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.
$ npx -y skills add kbanc85/claudia --skill memory-audit --agent claude-codeHow 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.mdname: 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
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
Terminal-based AI chief of staff. Remembers relationships, tracks commitments, helps you think strategically. Runs on Claude Code.
Repo: kbanc85/claudia
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