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v2.2-paseo-providers: Paseo provider stack + v2.2.1 pane-scoped chat fixes

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Ship Paseo-equivalent provider snapshot, AgentComposerBar, ACP dispatch
rewrite with streaming/persist, permission prompts, and agent commands.
Follow-up: pane-scoped chat resolution, CoderMessageList tool timeline,
WS user-delta replace, and inference orphan tool_call stripping.
Archive openspec v2-2; update CHANGELOG and CURRENT.

Co-authored-by: Cursor <cursoragent@cursor.com>
This commit is contained in:
indifferentketchup
2026-05-26 15:18:31 +00:00
parent 04673eaf59
commit 93d3f86c2b
96 changed files with 6694 additions and 1329 deletions
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97
apps/server/src/routes/skills.ts
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@@ -1,9 +1,13 @@
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';
import {
buildSkillInvokeSyntheticFrames,
DEFAULT_SKILL_USER_MESSAGE,
runSkillInvokeTransaction,
} from '../services/skill-invoke.js';
// Batch 9.6 slash-invoke handlers. Mirrors the MessageHandlers shape in
// routes/messages.ts so index.ts can pass thin adapters around broker +
@@ -35,8 +39,6 @@ const SkillInvokeBody = z.object({
user_message: z.string().max(64_000).nullable().optional(),
});
const DEFAULT_USER_MESSAGE = 'Apply this skill.';
export function registerSkillsRoutes(
app: FastifyInstance,
sql: Sql,
@@ -62,7 +64,9 @@ export function registerSkillsRoutes(
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 userText = parsed.data.user_message?.trim()
? parsed.data.user_message
: DEFAULT_SKILL_USER_MESSAGE;
const chatRows = await sql<Chat[]>`
SELECT id, session_id FROM chats WHERE id = ${req.params.id} AND status = 'open'
@@ -80,87 +84,20 @@ export function registerSkillsRoutes(
return { error: 'unknown_skill', message: `unknown skill: ${skill_name}` };
}
const toolCallId = randomUUID();
const toolCalls = [{ id: toolCallId, name: 'skill_use', args: { name: skill_name } }];
const toolResults = { tool_call_id: toolCallId, output: body, truncated: false };
const result = await sql.begin(async (tx) => {
const [synthAssistant] = await tx<{ id: string }[]>`
INSERT INTO messages (session_id, chat_id, role, content, status, created_at)
VALUES (${sessionId}, ${chat.id}, 'assistant', '', 'complete', clock_timestamp())
RETURNING id
`;
// v1.13.20: parts-only write. Single skill_use tool_call, no text
// content, so one part at seq 0.
await tx`
INSERT INTO message_parts (message_id, sequence, kind, payload)
VALUES (${synthAssistant!.id}, 0, 'tool_call', ${tx.json({
id: toolCallId,
name: 'skill_use',
args: { name: skill_name },
} as never)})
`;
const [toolMsg] = await tx<{ id: string }[]>`
INSERT INTO messages (session_id, chat_id, role, content, status, created_at)
VALUES (${sessionId}, ${chat.id}, 'tool', '', 'complete', clock_timestamp())
RETURNING id
`;
// v1.13.20: parts-only write of the synthetic tool result (skill body).
await tx`
INSERT INTO message_parts (message_id, sequence, kind, payload)
VALUES (${toolMsg!.id}, 0, 'tool_result', ${tx.json(toolResults as never)})
`;
const [userMsg] = await tx<{ id: string }[]>`
INSERT INTO messages (session_id, chat_id, role, content, status, created_at)
VALUES (${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,
};
const { result, toolCall } = await runSkillInvokeTransaction(sql, {
sessionId,
chatId: chat.id,
skillName: skill_name,
skillBody: body,
userText,
});
// 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,
});
for (const frame of buildSkillInvokeSyntheticFrames(chat.id, result, toolCall, body)) {
handlers.publishSessionFrame(sessionId, frame);
}
handlers.publishUserMessage(sessionId, chat.id, result.user_message_id, userText);
handlers.enqueueInference(sessionId, chat.id, result.assistant_message_id, 'default');