After verifying that the OpenClaw gateway's chat.send WebSocket RPC
accepts an 'attachments' array (confirmed from openclaw/openclaw source
and documentation), implement end-to-end image/file attachment support
for instance chat:
Bridge (openclaw-client.ts):
- chatSendAndWait() now accepts optional `attachments[]` parameter
- Passes attachments to chat.send RPC only when non-empty
Bridge (index.ts):
- /task-async accepts `attachments[]` from request body
- Forwards to chatSendAndWait unchanged
Backend (agent.controller.ts):
- executeInstanceTask() accepts IT0 attachment format
{ base64Data, mediaType, fileName? }
- Converts to OpenClaw format { name, mimeType, media: "data:..." }
- Saves attachments to conversation history via contextService
- Forwards to bridge via bridgeAttachments spread
Flutter (agent_instance_chat_remote_datasource.dart):
- createTask() now includes attachments in POST body when present
Flutter (chat_page.dart):
- Reverted Fix 5 (disabled button) — attachment button fully enabled
in instance mode since the bridge now supports it
Attachment format (OpenClaw wire):
{ name: string, mimeType: string, media: "data:<mime>;base64,<data>" }
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
## Changes
### openclaw-bridge: POST /skill-inject
- New endpoint writes SKILL.md to ~/.openclaw/skills/{name}/ inside the container volume
- OpenClaw gateway file watcher picks it up within 250ms (no restart needed)
- Optionally calls sessions.delete RPC after write so the next user message starts
a fresh session that loads the new skill directory immediately (zero-downtime)
- Path traversal guard on skill name (rejects names with / .. \)
- OPENCLAW_HOME env var configurable (default: /home/node/.openclaw)
### agent-service: POST /api/v1/agent/instances/:id/skills
- New endpoint in AgentInstanceController proxies skill injection requests to the
instance's bridge (http://{serverHost}:{hostPort}/skill-inject)
- Guards: instance must be 'running', serverHost/hostPort must be set, content ≤ 100KB
- iAgent calls this internally (localhost:3002) via Python urllib — no Kong auth needed
- sessionKey format for DingTalk users: "agent:main:dt-{dingTalkUserId}"
### agent-service: remove dead SkillManagerService
- Deleted skill-manager.service.ts (file-system .md loader, never called by anything)
- Removed from agent.module.ts provider list
- The live skill path is ClaudeAgentSdkEngine.loadTenantSkills() which reads directly
from the DB (it0_t_{tenantId}.skills) at task-execution time
### agent-service: clean up SystemPromptBuilder
- Removed unused skills?: string[] from SystemPromptContext (was never populated)
- Added clarifying comment: SDK engine handles skill injection, not this builder
## DB
- Inserted iAgent meta-skill "为小龙虾安装技能" into it0_t_default.skills
(id: 79ac23ed-78c2-4d5f-8652-a99cf5185b61)
- Content instructs iAgent to: query user instances → generate SKILL.md → call
POST /api/v1/agent/instances/:id/skills via Python urllib heredoc
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Bridge: tag isTimeout=true in timeout callbacks for semantic error routing
- Agent-service: show "⏳ 还在努力想呢" progress batchSend after 25s silence
- Agent-service: queue position feedback ("前面还有 N 条") via sessionWebhook
- Agent-service: buildErrorReply() maps timeout/disconnect/abort to distinct msgs
- Agent-service: instance status hints (stopped/starting/error) with action guidance
- Agent-service: all user-facing strings rewritten for conversational, friendly tone
- Agent-channel: pass isTimeout from bridge callback through to resolveCallbackReply
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
openclaw-bridge:
- index.ts: /task endpoint now calls chatSendAndWait() with idempotencyKey
(removes broken timeoutSeconds param; uses caller-supplied msgId for dedup)
- openclaw-client.ts: added onEvent() subscription + chatSendAndWait() that
subscribes to 'chat' WS events, waits for state='final' matching runId,
and extracts text from the message payload
dingtalk-router:
- After OAuth binding completes, sends a proactive greeting to the user via
DingTalk batchSend API (/v1.0/robot/oToMessages/batchSend) introducing the
agent by name and explaining what it can do
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
hailin