| name | claw-integration-design |
| description | Design and implement secure APIs and integration points for external AI bots and agents (OpenAI tool-calling, LangChain, OpenClaw). Use this skill whenever the user mentions agent integrations, tool manifests, bot API access, OAuth2 scopes for bots, webhook integrations, or designing endpoints for agentic workflows. Also trigger when users ask about securing bot writes or designing APIs for AI-powered automation. |
Bot/Agent Integration Design (Claw)
This skill provides guidelines and patterns for integrating web applications (SaaS/internal tools/products) with external bots and agent systems (e.g., OpenAI tool-calling, LangChain, OpenClaw). The goal is to allow agents to securely connect, read, and write data without turning the application itself into a bot.
Phase 1: Host Application Analysis
Adapt the integration to the project's existing domain model.
- Analyze the Application: Review
schema.prisma, models/, OpenAPI specs, or route definitions to understand the core resources (e.g., orders, products, leads).
- Select Exposure Targets: Decide which specific entities the agent actually needs access to for the task at hand.
Core Architectural Concepts
When building agent integrations based on your discovery, implement these foundational concepts:
1. Multi-Tenant Context
All read/write operations MUST be scoped to a specific tenant/workspace:
- Rule: Always require
tenant_id, org_id, or workspace_id in requests (via header, path, or body).
2. Domain-Specific Resource Model
Design endpoints that match the discovered entities exactly. Agents should write data directly to where it belongs:
- Do NOT use a generic
/items endpoint unless the application itself is a generic CMS.
- Do: Use specific, pluralized endpoints based on the domain (e.g.,
/v1/invoices, /v1/leads, /v1/candidates).
Authentication and Authorization
Authentication Methods
- MVP Validation: Use API Keys passed via the
Authorization: Bearer <API_KEY> header.
- Production Standard: Use OAuth2 (Authorization Code + PKCE) for integrations with third-party agent providers.
Scope / Permission Model (CRITICAL)
You MUST enforce a granular scope model based on the discovered resources using the {action}:{resource} pattern. Do not give agents root access.
Standard Scopes (Generic Examples):
read:{resource}: Read access to a specific resource (e.g., read:invoices).
write:{resource}: Access to create/update resources (e.g., write:leads).
admin:audit: Access to read audit logs.
High-Risk Scopes:
- Rule: Isolate riskier operations behind specific scopes, default off.
write:{resource}:delete: Permission to delete items (e.g., write:invoices:delete).
write:{resource}:bulk: Permission for bulk modifications.
Standard HTTP Guidelines
Enforce these standards on all agent-facing endpoints:
- Base Path:
/v1 (e.g., https://<domain>/v1)
- Content-Type:
application/json
- Rate Limiting: Implement rate limits (e.g., 60 req/min per key/token).
- Idempotency: Require an
Idempotency-Key header (UUID) for all POST (create) endpoints.
- Agent Traceability: Suggest headers like
X-Agent-Name (e.g., openclaw, langchain) and X-Trace-Id for log correlation.
Standard API Endpoints
When setting up the API, implement these minimal required endpoints dynamically based on Phase 1 discovery.
1. Health and Meta
GET /v1/health: Returns { "status": "ok", "version": "0.1.0" }.
GET /v1/openapi.json: Serve the OpenAPI spec so agents can auto-generate tools.
2. Exposed Resources (CRUD)
For every entity you decided to expose in Phase 1 (e.g., invoices):
- List:
GET /v1/{resource}?tenant_id=...&status=open (Scope: read:{resource})
- Read:
GET /v1/{resource}/{id} (Scope: read:{resource})
- Create:
POST /v1/{resource} (Scope: write:{resource}, require Idempotency-Key)
- Update:
PATCH /v1/{resource}/{id} (Scope: write:{resource})
- Delete:
DELETE /v1/{resource}/{id} (Requires specialized scope write:{resource}:delete)
3. Search (Crucial for Agents)
- Endpoint:
GET /v1/search?tenant_id=...&q=...&types={resource1},{resource2}
- MVP: SQL Full-Text Search (PostgreSQL
tsvector, SQLite FTS5).
- V2 — Semantic Search: Use embedding models (e.g.,
text-embedding-3-small from OpenAI, or nomic-embed-text locally) to generate vectors, stored in a vector DB:
- Managed: Pinecone, Weaviate, Qdrant Cloud
- Self-hosted / Postgres-native:
pgvector extension (lowest ops overhead for most projects)
- Endpoint:
POST /v1/semantic-search { text, types, limit, threshold }
- When to use V2: When keyword search fails for paraphrased queries or conceptually similar content.
See references/oauth2-flow.md for auth setup and assets/tools-manifest-template.json for a ready-to-use manifest.
4. Links (Relationships)
If the domain model is highly relational (e.g., an invoice belongs to a customer):
- Endpoint:
POST /v1/links
- Scope:
write:links
- Payload:
tenant_id, from_id, to_id, relation (e.g., belongs_to).
5. Audit Logging
- Endpoint:
GET /v1/audit
- Scope:
admin:audit
- Keep a detailed log of actor (
agent_name), action (e.g., create_invoice), target, and trace_id.
Standard Error Formatting
Always return errors in this consistent format for predictability:
{
"error": {
"code": "insufficient_scope",
"message": "write:invoices scope required",
"details": { "required": ["write:invoices"] }
}
}
Common codes: unauthorized, insufficient_scope, not_found, validation_error, rate_limited, conflict, internal_error.
Agent Manifest (tools.json)
When requested to build a tool manifest for an agent framework, use the ready-to-use template at:
assets/tools-manifest-template.json
The template includes definitions for search_[RESOURCE_NAME]s, create_[RESOURCE_NAME], update_[RESOURCE_NAME], and create_link. Replace <your-domain> with the actual API base URL.
Key manifest conventions:
- Use
"type": "bearer" for auth
- Always include
tenant_id as a required field in every tool's input_schema
- Keep
description fields agent-friendly — they guide LLM tool selection
Internal Data Tracking
Every record/capture created by an agent MUST trace back to its origin. Add these fields to database schemas:
source: Should indicate agent (vs human).
agent_name: Identifying name of the bot.
trace_id: For request correlation.
metadata: Flexible JSON column for arbitrary agent state/data.