feat(server): skills v1 — parser, tools, /api/skills, mount

- /data/skills mount (host: /opt/skills)
- skill_find, skill_use, skill_resource added to default read-only
  tool set; opt-in for agents with explicit tools: whitelist
- AGENTS.md builtin agents drop explicit tools: arrays to inherit
  the new default (now includes skill tools)
- POST /api/chats/:id/skill_invoke for slash-command flow
- 19 SKILL.md files seeded at /opt/skills/ across 6 source groups

apps/server/src/routes/skills.ts

@@ -0,0 +1,156 @@
+import { randomUUID } from 'node:crypto';
+import type { FastifyInstance } from 'fastify';
+import { z } from 'zod';
+import type { Sql } from '../db.js';
+import type { Chat } from '../types/api.js';
+import { getSkillBody, listSkills } from '../services/skills.js';
+
+// Batch 9.6 slash-invoke handlers. Mirrors the MessageHandlers shape in
+// routes/messages.ts so index.ts can pass thin adapters around broker +
+// inference runner without skills.ts importing them directly.
+export interface SkillInvokeHandlers {
+  enqueueInference: (
+    sessionId: string,
+    chatId: string,
+    assistantMessageId: string,
+    user: string,
+  ) => void;
+  publishUserMessage: (
+    sessionId: string,
+    chatId: string,
+    userMessageId: string,
+    content: string,
+  ) => void;
+  publishSessionFrame: (
+    sessionId: string,
+    frame: Record<string, unknown> & { type: string },
+  ) => void;
+}
+
+const SkillInvokeBody = z.object({
+  skill_name: z.string().min(1),
+  // Optional — server fills in a default if absent or whitespace-only so the
+  // model always has something to act on (matches the spec's "Apply this
+  // skill." filler).
+  user_message: z.string().max(64_000).nullable().optional(),
+});
+
+const DEFAULT_USER_MESSAGE = 'Apply this skill.';
+
+export function registerSkillsRoutes(
+  app: FastifyInstance,
+  sql: Sql,
+  handlers: SkillInvokeHandlers,
+): void {
+  // Debug/admin surface — the model interacts with skills via the three
+  // skill_* tools, not through this endpoint.
+  app.get('/api/skills', async () => {
+    return { skills: await listSkills() };
+  });
+
+  // POST /api/chats/:id/skill_invoke — slash-command entry point. Loads the
+  // skill body server-side (clients never get to forge file content),
+  // persists 4 messages in one transaction (synthetic assistant tool_use,
+  // synthetic tool result, real user message, streaming assistant), and
+  // enqueues inference against the updated history.
+  app.post<{ Params: { id: string } }>(
+    '/api/chats/:id/skill_invoke',
+    async (req, reply) => {
+      const parsed = SkillInvokeBody.safeParse(req.body);
+      if (!parsed.success) {
+        reply.code(400);
+        return { error: 'invalid body', details: parsed.error.flatten() };
+      }
+      const { skill_name } = parsed.data;
+      const userText = parsed.data.user_message?.trim() ? parsed.data.user_message : DEFAULT_USER_MESSAGE;
+
+      const chatRows = await sql<Chat[]>`
+        SELECT id, session_id FROM chats WHERE id = ${req.params.id} AND status = 'open'
+      `;
+      if (chatRows.length === 0) {
+        reply.code(404);
+        return { error: 'chat not found' };
+      }
+      const chat = chatRows[0]!;
+      const sessionId = chat.session_id;
+
+      const body = await getSkillBody(skill_name);
+      if (body === null) {
+        reply.code(404);
+        return { error: 'unknown_skill', message: `unknown skill: ${skill_name}` };
+      }
+
+      const toolCallId = randomUUID();
+      const toolCalls = [{ id: toolCallId, name: 'skill_use', args: { name: skill_name } }];
+      const toolResults = { tool_call_id: toolCallId, output: body, truncated: false };
+
+      const result = await sql.begin(async (tx) => {
+        const [synthAssistant] = await tx<{ id: string }[]>`
+          INSERT INTO messages (session_id, chat_id, role, content, tool_calls, status, created_at)
+          VALUES (${sessionId}, ${chat.id}, 'assistant', '', ${sql.json(toolCalls as never)}, 'complete', clock_timestamp())
+          RETURNING id
+        `;
+        const [toolMsg] = await tx<{ id: string }[]>`
+          INSERT INTO messages (session_id, chat_id, role, content, tool_results, status, created_at)
+          VALUES (${sessionId}, ${chat.id}, 'tool', '', ${sql.json(toolResults as never)}, 'complete', clock_timestamp())
+          RETURNING id
+        `;
+        const [userMsg] = await tx<{ id: string }[]>`
+          INSERT INTO messages (session_id, chat_id, role, content, status, created_at)
+          VALUES (${sessionId}, ${chat.id}, 'user', ${userText}, 'complete', clock_timestamp())
+          RETURNING id
+        `;
+        const [assistantMsg] = await tx<{ id: string }[]>`
+          INSERT INTO messages (session_id, chat_id, role, content, status, created_at)
+          VALUES (${sessionId}, ${chat.id}, 'assistant', '', 'streaming', clock_timestamp())
+          RETURNING id
+        `;
+        await tx`UPDATE sessions SET updated_at = clock_timestamp() WHERE id = ${sessionId}`;
+        await tx`UPDATE chats SET updated_at = clock_timestamp() WHERE id = ${chat.id}`;
+        return {
+          synth_assistant_id: synthAssistant!.id,
+          tool_message_id: toolMsg!.id,
+          user_message_id: userMsg!.id,
+          assistant_message_id: assistantMsg!.id,
+        };
+      });
+
+      // Synthetic frames so useSessionStream's reducer reflects the new
+      // history without a refetch. Frame shapes match the streaming-inference
+      // protocol (see services/inference.ts InferenceFrame).
+      handlers.publishSessionFrame(sessionId, {
+        type: 'message_started',
+        message_id: result.synth_assistant_id,
+        chat_id: chat.id,
+        role: 'assistant',
+      });
+      handlers.publishSessionFrame(sessionId, {
+        type: 'tool_call',
+        message_id: result.synth_assistant_id,
+        chat_id: chat.id,
+        tool_call: toolCalls[0]!,
+      });
+      handlers.publishSessionFrame(sessionId, {
+        type: 'message_complete',
+        message_id: result.synth_assistant_id,
+        chat_id: chat.id,
+      });
+      // The tool_result frame's reducer branch creates the tool-role message
+      // in-place when it doesn't already exist — no separate message_started
+      // is needed for the tool side.
+      handlers.publishSessionFrame(sessionId, {
+        type: 'tool_result',
+        tool_message_id: result.tool_message_id,
+        tool_call_id: toolCallId,
+        chat_id: chat.id,
+        output: body,
+        truncated: false,
+      });
+      handlers.publishUserMessage(sessionId, chat.id, result.user_message_id, userText);
+      handlers.enqueueInference(sessionId, chat.id, result.assistant_message_id, 'default');
+
+      reply.code(202);
+      return result;
+    },
+  );
+}