Agent Skill
2/7/2026

memories-sanitize

Review recent memories and remove invalid or misleading ones from the semantic memory database

M
mahmoudimus
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SKILL.md

Namememories-sanitize
DescriptionReview recent memories and remove invalid or misleading ones from the semantic memory database

name: memories-sanitize description: Review recent memories and remove invalid or misleading ones from the semantic memory database allowed-tools: Bash(simba *)

Memory Sanitization Procedure

Review memories and identify those that are invalid, misleading, or outdated. This applies to any work session - debugging, feature development, refactoring, exploration, etc.

Step 1: List Memories

List all memories:

simba memory list

Or filter by type:

simba memory list --type GOTCHA

Each memory shows: id, type, confidence, and content.

Step 2: Identify Invalid Memories

Review each memory and mark as INVALID if it:

From Any Session Type

  1. Outdated information - Was true but no longer applies after changes
  2. Superseded by better approach - A newer, better solution exists
  3. Too specific/narrow - Only applied to a removed/changed feature
  4. Incorrect generalization - Specific case wrongly stated as general rule

From Debugging Sessions

  1. Red herring - An initial hypothesis that turned out to be wrong
  2. Wrong blame - Points to code that was actually working correctly
  3. Non-issue - Something suspected as a bug but wasn't

From Feature Development

  1. Abandoned approach - Design decision that was later reversed
  2. Prototype artifact - Workaround that was replaced by proper implementation
  3. Incomplete understanding - Early assumption corrected by later work

Step 3: Delete Invalid Memories

For each invalid memory, delete it:

simba memory delete <MEMORY_ID>

Step 4: Add Corrected Memories (Optional)

If an invalid memory should be replaced with a correct version:

simba memory store --type WORKING_SOLUTION --content "<CORRECT_LEARNING>" --context "<CONTEXT>" --confidence 0.95

Memory Types Reference

TypeUse For
GOTCHACounterintuitive behaviors, traps, "watch out for this"
WORKING_SOLUTIONCommands, code, or approaches that worked
PATTERNRecurring architectural decisions or workflows
DECISIONExplicit design choices with reasoning
FAILUREWhat didn't work and why (useful to avoid repeating)
PREFERENCEUser's stated preferences

Examples

Debugging Example

Invalid: "Reference equality vs .Equals() mismatch causes graph disconnection" Correct: "Coordinate tolerance 1e-6 too small for reprojected coords; use 0.01m for EPSG:3857"

Feature Development Example

Invalid: "Use polling for real-time updates in dashboard" Correct: "Use WebSocket for real-time updates - polling caused excessive server load"

Refactoring Example

Invalid: "ServiceLocator pattern works well for dependency injection" Correct: "Constructor injection preferred - ServiceLocator made testing difficult"

Tips

  • Wait until work is complete before extracting memories
  • During iterative development, early decisions often get revised
  • Lower confidence scores for findings that might change
  • Be specific in context field about file paths and scenarios
  • Periodic sanitization prevents memory database pollution
Skills Info
Original Name:memories-sanitizeAuthor:mahmoudimus