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Store user preferences, learnings from tasks, and procedure outcomes. Use to remember what works and recall context before new tasks. (user)
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Based on SOC occupation classification
Complete Hindsight documentation for AI agents. Use this to learn about Hindsight architecture, APIs, configuration, and best practices.
Review changed code against project standards. Checks for missing tests, dead code, type safety, lint issues, and coding conventions. Run after completing any implementation work.
Search long-term memory for relevant context from past coding sessions using Hindsight MCP tools
Cut a core Hindsight release (vX.Y.Z) and open the changelog + blog PR. Use when asked to cut/start a release, bump the version, or publish a new Hindsight version.
Create a new Hindsight-powered subagent with long-term memory. Use when the user wants a specialized agent that learns and remembers across sessions.
Expert memory architect. Understands your application, identifies where memory adds value, and produces an implementation plan with bank config, tag schema, and code.
| name | hindsight-local |
| description | Store user preferences, learnings from tasks, and procedure outcomes. Use to remember what works and recall context before new tasks. (user) |
You have persistent memory via the hindsight-embed CLI. Proactively store learnings and recall context to provide better assistance.
Before using memory commands, verify Hindsight is configured:
uvx hindsight-embed daemon status
If this fails or shows "not configured", run the interactive setup:
uvx hindsight-embed configure
This will prompt for an LLM provider and API key. After setup, the commands below will work.
When you call retain, Hindsight does not store the string as-is. The server runs an internal pipeline that:
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.
Use memory retain to store what you learn. Pass the full context — raw observations, session notes, conversation excerpts, or detailed descriptions:
uvx hindsight-embed memory retain default "User is working on a TypeScript project. They enabled strict mode and prefer explicit type annotations over inference."
uvx hindsight-embed memory retain default "Ran the test suite with NODE_ENV=test. Tests pass. Without NODE_ENV=test, the suite fails with a missing config error." --context procedures
uvx hindsight-embed memory retain default "Build failed on Node 18 with error 'ERR_UNSUPPORTED_ESM_URL_SCHEME'. Switched to Node 20 and build succeeded." --context learnings
You can also pass a raw conversation transcript with timestamps:
uvx hindsight-embed memory retain default "[2026-03-16T10:12:03] User: The auth tests keep failing on CI but pass locally. Any idea?
[2026-03-16T10:12:45] Assistant: Let me check the CI logs. Looks like the tests are running without the TEST_DATABASE_URL env var set — they fall back to the production DB URL and hit a connection timeout.
[2026-03-16T10:13:20] User: Ah right, I never added that to the CI secrets. Adding it now.
[2026-03-16T10:15:02] User: That fixed it. All green now." --context learnings
Use memory recall BEFORE starting tasks to get relevant context:
uvx hindsight-embed memory recall default "user preferences for this project"
uvx hindsight-embed memory recall default "what issues have we encountered before"
Use memory reflect to synthesize context:
uvx hindsight-embed memory reflect default "How should I approach this task based on past experience?"
Always store after you learn something valuable:
Always recall before:
--context for metadata: The --context flag labels the type of memory (e.g., procedures, learnings, preferences), not a replacement for full content