hindsight-local
Store user preferences, learnings from tasks, and procedure outcomes. Use to remember what works and recall context before new tasks. (user)
By vectorize-io · 387 installs
npx skills add vectorize-io/hindsight --skill hindsight-local
Source repository · Upstream listing
Hindsight Memory Skill (Local)
You have persistent memory via the hindsight embed CLI. Proactively store learnings and recall context to provide better assistance.
Setup Check (First Time Only)
Before using memory commands, verify Hindsight is configured:
If this fails or shows "not configured" , run the interactive setup:
This will prompt for an LLM provider and API key. After setup, the commands below will work.
How Hindsight Works
When you call retain , Hindsight does not store the string as is. The server runs an internal pipeline that:
1. Extracts structured facts from the content using an LLM
2. Identifies entities (people, tools, concepts) and links related facts
3. Builds temporal and causal relationships between facts
4. Generates embeddings for semantic search
This means you should pass rich, full context content — the server is better at extracting what matters than a pre summarized string. Your job is to decide when to store, not what to extract.
Commands
Store a memory
Use memory retain to store what you learn. Pass the full context — raw observations, session notes, conversation excerpts, or detailed descriptions:
You can also pass a raw conversation transcript with timestamps:
Recall memories
Use memory recall BEFORE starting tasks to get relevant context:
Reflect on memories
Use memory reflect to synthesize context:
IMPORTANT: When to Store Memories
Always store after you learn something valuable:
User Preferences
Coding style (indentation, naming conventions, language preferences)
Tool preferences (editors, linters, formatters)
Communication preferences
Project conventions
Procedure Outcomes
Steps that successfully completed a task
Commands that worked (or failed) and why
Workarounds discovered
Configuration that resolved issues
Learnings from Tasks
Bugs encountered and their solutions
Performance optimizations that worked
Architecture decisions and rationale
Dependencies or version requirements
IMPORTANT: When to Recall Memories
Always recall before:
Starting any non trivial task
Making decisions about implementation
Suggesting tools, libraries, or approaches
Writing code in a new area of the project
Best Practices
1. Store immediately : When you discover something, store it right away
2. Pass rich context : Include full observations, not pre summarized strings — the server extracts facts automatically
3. Include outcomes : Store what happened AND why, including failures and workarounds
4. Recall first : Always check for relevant context before starting work
5. Use context for metadata : The context flag labels the type of memory (e.g., procedures , learnings , preferences ), not a replacement for full content