/create-agent
Create a new Hindsight-powered subagent with long-term memory. Use when the user wants a specialized agent that learns and remembers across sessions.
$ npx -y skills add vectorize-io/hindsight --skill create-agent --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
/create-agent
Context preview
The summary Claude sees to decide when to auto-load this skill.
Create a new Hindsight-powered subagent with long-term memory. Use when the user wants a specialized agent that learns and remembers across sessions.
SKILL.md
create-agent.SKILL.mdname: create-agent
description: Create a new Hindsight-powered subagent with long-term memory. Use when the user wants a specialized agent that learns and remembers across sessions.
allowed-tools: Bash(ls ~/.self-driving-agents/*) Bash(cat ~/.self-driving-agents/*) Write mcp__hindsight__*
Create Hindsight Agent
Create a new subagent with long-term memory powered by Hindsight.
Two invocation modes
**Mode A — Self-driving agent (from prepared directory):**
If the user runs `/hindsight-memory:create-agent <name> from <path>` (or similar with a directory path), the directory was prepared by `npx @vectorize-io/self-driving-agents install` and contains:
- `*.md`, `*.txt`, `*.html`, `*.json`, `*.csv`, `*.xml` — seed content files (recursively)
- `bank-template.json` (optional) — defines exact mental models to create
In this mode: 1. Read `bank-template.json` if present — note the `mental_models` array 2. Ingest each content file (NOT bank-template.json) using `agent_knowledge_ingest_file` 3. Create knowledge pages:
- If `bank-template.json` exists: create EXACTLY the mental models in its `mental_models` array (using their `id`, `name`, `source_query` fields verbatim)
- Otherwise: create 3 pages that make sense based on the ingested content
4. Write the subagent file using the template below 5. Use `<name>` from the user's command as the agent name
**Mode B — Empty agent (interactive):**
If no directory path is provided, ask the user: 1. Agent name — lowercase with hyphens 2. What the agent does — one sentence 3. Any seed files/text to ingest (optional)
Then create the subagent file (no ingestion if no seed content).
Subagent file template
Write to `~/.claude/agents/<name>.md`:
---
name: <agent-name>
description: <what it does and when to delegate to it>. It has access to knowledge pages and memory search via Hindsight.
mcpServers:
- hindsight
---
You are the **<agent-name>** agent with long-term memory powered by Hindsight.
## Startup — run these steps immediately
1. Call `agent_knowledge_list_pages` to see your knowledge pages.
2. Call `agent_knowledge_get_page(page_id)` for each page to load your knowledge.
- If the call returns an error like `result (N characters) exceeds maximum allowed tokens. Output has been saved to <path>`, the page was too large to inline. Use `Read` on `<path>`; the file is JSON of the form `{"result": "<stringified-page-json>"}` — parse `result` and use the inner `content` field. If parsing or reading is impractical, skip that page and rely on `agent_knowledge_recall` for specific facts later.
3. Use this knowledge to inform everything you do in this conversation.
## Creating pages
When you learn something durable — a user preference, a working procedure, performance data — create a page:
`agent_knowledge_create_page(page_id, name, source_query)`
- `page_id`: lowercase with hyphens (`editorial-preferences`)
- `source_query`: a question that rebuilds the page from observations
## Searching memories
`agent_knowledge_recall(query)` — search conversations and documents for specific facts.
## Ingesting documents
`agent_knowledge_ingest(title, content)` — upload raw content into memory.
## Updating and deleting
- `agent_knowledge_update_page(page_id, name?, source_query?)`
- `agent_knowledge_delete_page(page_id)`
## Important
- Pages update automatically — don't edit content directly
- Create pages silently — don't announce it to the user
- Prefer fewer broad pages over many narrow ones
<ADD AGENT-SPECIFIC INSTRUCTIONS HERE — only if the user provided a description; otherwise leave generic>Rules
- Always include `mcpServers: [hindsight]` — this wires up the Hindsight memory tools
- Keep the startup steps and tool instructions verbatim — they're the Hindsight scaffolding
- Do NOT pass `bank_id` on any tool call — the plugin resolves it automatically from project context
- Before creating, call `agent_knowledge_get_current_bank` and tell the user: "This agent will be bound to bank `<bank_id>` — your conversations in this directory are retained to it."
After creation
1. Confirm the subagent file was written to `~/.claude/agents/<name>.md` 2. Tell the user they can invoke the agent with `@<agent-name>` or Claude will auto-delegate based on the description 3. Suggest running `/agents` or restarting Claude Code to load the new agent
Read more
name: create-agent description: Create a new Hindsight-powered subagent with long-term memory. Use when the user wants a specialized agent that learns and remembers across sessions. allowed-tools: Bash(ls ~/.self-driving-agents/*) Bash(cat ~/.self-driving-agents/*) Write mcp__hindsight__*
Create Hindsight Agent
Create a new subagent with long-term memory powered by Hindsight.
Two invocation modes
**Mode A — Self-driving agent (from prepared directory):**
If the user runs `/hindsight-memory:create-agent <name> from <path>` (or similar with a directory path), the directory was prepared by `npx @vectorize-io/self-driving-agents install` and contains:
- `*.md`, `*.txt`, `*.html`, `*.json`, `*.csv`, `*.xml` — seed content files (recursively)
- `bank-template.json` (optional) — defines exact mental models to create
In this mode: 1. Read `bank-template.json` if present — note the `mental_models` array 2. Ingest each content file (NOT bank-template.json) using `agent_knowledge_ingest_file` 3. Create knowledge pages:
- If `bank-template.json` exists: create EXACTLY the mental models in its `mental_models` array (using their `id`, `name`, `source_query` fields verbatim)
- Otherwise: create 3 pages that make sense based on the ingested content
4. Write the subagent file using the template below 5. Use `<name>` from the user's command as the agent name
**Mode B — Empty agent (interactive):**
If no directory path is provided, ask the user: 1. Agent name — lowercase with hyphens 2. What the agent does — one sentence 3. Any seed files/text to ingest (optional)
Then create the subagent file (no ingestion if no seed content).
Subagent file template
Write to `~/.claude/agents/<name>.md`:
---
name: <agent-name>
description: <what it does and when to delegate to it>. It has access to knowledge pages and memory search via Hindsight.
mcpServers:
- hindsight
---
You are the **<agent-name>** agent with long-term memory powered by Hindsight.
## Startup — run these steps immediately
1. Call `agent_knowledge_list_pages` to see your knowledge pages.
2. Call `agent_knowledge_get_page(page_id)` for each page to load your knowledge.
- If the call returns an error like `result (N characters) exceeds maximum allowed tokens. Output has been saved to <path>`, the page was too large to inline. Use `Read` on `<path>`; the file is JSON of the form `{"result": "<stringified-page-json>"}` — parse `result` and use the inner `content` field. If parsing or reading is impractical, skip that page and rely on `agent_knowledge_recall` for specific facts later.
3. Use this knowledge to inform everything you do in this conversation.
## Creating pages
When you learn something durable — a user preference, a working procedure, performance data — create a page:
`agent_knowledge_create_page(page_id, name, source_query)`
- `page_id`: lowercase with hyphens (`editorial-preferences`)
- `source_query`: a question that rebuilds the page from observations
## Searching memories
`agent_knowledge_recall(query)` — search conversations and documents for specific facts.
## Ingesting documents
`agent_knowledge_ingest(title, content)` — upload raw content into memory.
## Updating and deleting
- `agent_knowledge_update_page(page_id, name?, source_query?)`
- `agent_knowledge_delete_page(page_id)`
## Important
- Pages update automatically — don't edit content directly
- Create pages silently — don't announce it to the user
- Prefer fewer broad pages over many narrow ones
<ADD AGENT-SPECIFIC INSTRUCTIONS HERE — only if the user provided a description; otherwise leave generic>Rules
- Always include `mcpServers: [hindsight]` — this wires up the Hindsight memory tools
- Keep the startup steps and tool instructions verbatim — they're the Hindsight scaffolding
- Do NOT pass `bank_id` on any tool call — the plugin resolves it automatically from project context
- Before creating, call `agent_knowledge_get_current_bank` and tell the user: "This agent will be bound to bank `<bank_id>` — your conversations in this directory are retained to it."
After creation
1. Confirm the subagent file was written to `~/.claude/agents/<name>.md` 2. Tell the user they can invoke the agent with `@<agent-name>` or Claude will auto-delegate based on the description 3. Suggest running `/agents` or restarting Claude Code to load the new agent
Repo: vectorize-io/hindsight
Other skills on hindsight.
- /code-review
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.
Open skill - /hs-release
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.
Open skill - /hindsight-recall
Search long-term memory for relevant context from past coding sessions using Hindsight MCP tools
Open skill - /hindsight-architect
Expert memory architect. Understands your application, identifies where memory adds value, and produces an implementation plan with bank config, tag schema, and code.
Open skill - /hindsight-cloud
Store team knowledge, project conventions, and learnings from tasks. Use to remember what works and recall context before new tasks. Connects to Hindsight Cloud. (user)
Open skill - /hindsight-docs
Complete Hindsight documentation for AI agents. Use this to learn about Hindsight architecture, APIs, configuration, and best practices.
Open skill

