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hindsight-local

Store preferences, task lessons, and procedure outcomes in Hindsight, then retrieve relevant context before starting new work. It records detailed observations and can synthesize past experience into guidance for approaching the next task.

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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)

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适用场景

  • Remembering preferences and project conventions
  • Recording bug fixes and workarounds
  • Keeping successful and failed procedure outcomes
  • Reviewing past experience before starting a task

包含的文件(1)

  • SKILL.md4.4 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

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:

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.

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:

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

Recall memories

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"

Reflect on memories

Use memory reflect to synthesize context:

uvx hindsight-embed memory reflect default "How should I approach this task based on past experience?"

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

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同一仓库的技能

Record task handoffs between Bots in shared Hindsight memory, including progress, remaining work, sources, and caveats. Other Bots can retrieve the record later, continue unfinished work, and report the outcome back through shared memory.

中文简介正在准备中。当前显示英语简介。

  • Handing unfinished work to another Bot
  • Resuming a task started by another Bot
  • Sharing findings with Bots outside the current conversation
vectorize-io/hindsight5.2万2026年10月19日 更新

Review changed code against project rules and report missing tests, unused code, typing problems, and style violations. It also checks API design and data isolation, helping developers identify issues after implementation.

中文简介正在准备中。当前显示英语简介。

  • Reviewing changes after implementation
  • Finding missing tests and unused code
  • Checking Python types and API design
vectorize-io/hindsight5.2万2026年10月19日 更新

Create a specialized Claude Code subagent with Hindsight long-term memory. Start with an empty agent or import prepared documents, then equip it with knowledge pages and memory search to reuse information across sessions.

中文简介正在准备中。当前显示英语简介。

  • Create a specialized agent that remembers across sessions
  • Build an agent from prepared reference documents
  • Start an empty agent and add knowledge over time
vectorize-io/hindsight5.2万2026年10月19日 更新

figure

免费

Create an animated diagram showing request flows, background jobs, or feature changes. The result is a single SVG image for README files, pull requests, issues, or blog posts, with support for light and dark themes.

中文简介正在准备中。当前显示英语简介。

  • Explaining request and data flows
  • Illustrating how a background job works
  • Showing feature changes in a pull request
vectorize-io/hindsight5.2万2026年10月19日 更新

Plan how an AI application should use Hindsight memory. Identify useful information to retain, define user-scoping tags and memory bank settings, and specify how retrieved facts and synthesized knowledge should reach the model.

中文简介正在准备中。当前显示英语简介。

  • Plan memory that carries conversation context across sessions
  • Design tags that separate each user's memories
  • Plan summaries of customer preferences and recurring issues
vectorize-io/hindsight5.2万2026年10月19日 更新

Store project conventions, task outcomes, and troubleshooting lessons in a shared Hindsight Cloud memory bank. Retrieve relevant context before new work, or synthesize past experience to guide decisions and help teammates reuse what has been learned.

中文简介正在准备中。当前显示英语简介。

  • Save project coding and testing conventions
  • Share failure causes, fixes, and workarounds
  • Retrieve related lessons before starting a task
vectorize-io/hindsight5.2万2026年10月19日 更新

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