Skill: erikashby/ai-specialists (version 1.1.0)

--- name: ai-specialists description: Interact with AI Specialists via the AI Specialists Hub MCP endpoint. Use when the user asks about any of their AI specialists (e.g. Ruby, Peter, Benjamin, Marty), wants to read/write specialist documents, manage meal plans, check specialist workspaces, hire/dismiss specialists, or work with any MCP-connected specialist. Also use when the user mentions "specialist", "AI specialist", "MCP", or refers to a specialist by name. --- # AI Specialists Hub - MCP Integration ## Connection Call the MCP endpoint via HTTP POST. The endpoint URL is stored in TOOLS.md or provided by the user. ```bash curl -s -X POST "$MCP_URL" \ -H "Content-Type: application/json" \ -H "Accept: application/json, text/event-stream" \ -d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"TOOL_NAME","arguments":{...}}}' ``` **Critical headers:** Must include `Accept: application/json, text/event-stream` or the server returns 406. **Response format:** SSE — parse with: `response.split('data: ')[1]` → JSON → `result.content[0].text` ## Available Tools ### Discovery & Management | Tool | Required Params | Description | |------|----------------|-------------| | `list_specialists` | — | List all hired specialists | | `list_specialist_types` | — | List available specialist types | | `hire_specialist` | `type`, `name` | Hire a new specialist | | `dismiss_specialist` | `specialist` | Remove a specialist | | `import_specialist` | `url` | Import from GitHub URL | | `get_specialist_overview` | `specialist` | Get specialist summary | ### Workspace Navigation | Tool | Required Params | Description | |------|----------------|-------------| | `explore_specialist_tree` | `specialist` | Full folder/file tree | | `list_specialist_folder` | `specialist`, `folder_path` | List folder contents | ### Document Operations | Tool | Required Params | Description | |------|----------------|-------------| | `read_specialist_document` | `specialist`, `document_path` | Read one document | | `read_specialist_documents` | `specialist`, `document_paths` (array) | Bulk read multiple docs | | `update_specialist_document` | `specialist`, `document_path`, `content` | Create or update a doc | | `delete_specialist_document` | `specialist`, `document_path` | Delete a document | ### Folder Operations | Tool | Required Params | Description | |------|----------------|-------------| | `create_specialist_folder` | `specialist`, `folder_path` | Create folder (recursive) | | `delete_specialist_folder` | `specialist`, `folder_path` | Delete folder and contents | **Parameter note:** The specialist identifier is always the `id` field from `list_specialists`, not the display name. Use lowercase (e.g. `ruby`, `peter`, `benjamin`). ## Working with a Specialist Every specialist has an `ai-instructions/` folder containing their identity and behavioral instructions. **Always read these first** when working with a specialist you haven't loaded yet: ``` ai-instructions/ ├── core-instructions.md # Who they are, what they do, how they behave └── getting_started.md # Initialization sequence, workspace structure ``` ### Pattern: First interaction with a specialist 1. `list_specialists` → find the specialist id 2. `read_specialist_documents` → read `ai-instructions/core-instructions.md` and `ai-instructions/getting_started.md` 3. Understand their domain, workspace structure, and communication style 4. `explore_specialist_tree` → see their full workspace 5. Now you can work with their data informed by their context ### Pattern: Quick data retrieval 1. `explore_specialist_tree` → find the files you need 2. `read_specialist_documents` → bulk read (more efficient than individual reads) 3. Summarize for the user ### Pattern: Updating specialist data 1. Read the existing document first 2. Modify content as needed 3. `update_specialist_document` → write back (creates if new, overwrites if existing) 4. For new folders: `create_specialist_folder` first, then write documents into it ## User Signup (Agent-Initiated Onboarding) If your human doesn't have an AI Specialists Hub account yet, you can create one via the public signup API: ```bash curl -s -X POST "https://aispecialistshub.com/api/v1/signup" \ -H "Content-Type: application/json" \ -d '{"username":"<username>","email":"<email>","password":"<password>"}' ``` **Response (201):** ```json { "username": "...", "mcpKey": "...", "accountStatus": "unverified", "specialistLimit": 2, "message": "..." } ``` ### ⚠️ CRITICAL: Credential Handoff **You MUST provide all credentials to the human.** Whether you auto-generate the username/email/password or ask the human to choose them, the human must receive: 1. **Username** — for web dashboard login at aispecialistshub.com 2. **Email** — used for account verification 3. **Password** — for web dashboard login 4. **MCP key** — for connecting AI tools to their specialists Never keep credentials from the human. They own the account. Present all four clearly after signup. ### Unverified Accounts - Limited to **2 specialists** (default: Friday is auto-hired) - Full MCP access — specialists work immediately - Can log in to web dashboard with username/password - Verify email for full access (more specialists) ### Signup Flow 1. Confirm the human wants an AI Specialists Hub account 2. Collect or generate: username, email, password 3. Call `POST /api/v1/signup` 4. **Give the human ALL credentials** (username, email, password, MCP key) 5. Store the MCP endpoint URL in your config: `https://aispecialistshub.com/api/v1/mcp/<username>/<mcpKey>` 6. Start using specialists via MCP ## Configuration Store the MCP endpoint URL in TOOLS.md: ```markdown ### AI Specialists Hub - MCP endpoint: https://aispecialistshub.com/api/v1/mcp/<user>/<key> ``` See `references/specialists-guide.md` for details on specialist workspace conventions.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: suspicious (HIGH)