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DottaandPaperclip
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## Thinking Path > - Paperclip is the open source app people use to manage AI agents for work. > - Standing chats show recent messages and current task questions. > - Recent-message pagination bounds history work, but it does not bound question work. > - The question read built the full company attention feed before it selected the chat's tasks. > - Each feed read also checked seeded queue membership with one insert per item. > - This pull request scopes question collection in the attention owner and batches queue membership checks. > - Chats keep their current question cards and initial layout while doing less work. ## Linked Issues or Issue Description Follow-up to #18358 and #18323. Related work: #18312. **What happened?** A hosted standing chat remained slow after recent-message pagination shipped. On commit `4eaa435bf4`, an embedded-browser reload made the conversation usable at about 8.6 seconds. Recent comments finished at about 1.9 seconds. The pending-question request held the initial reveal until about 8.4 seconds. That request called the complete company attention feed and then filtered its results. The separate badge summary also did broad work. **Expected behavior** Chat question cost should depend on the relevant tasks. Reading an existing queue must not require a separate insert for every member. Current access and decision policy must remain in force. **Steps to reproduce** 1. Create a standing chat with questions on tasks assigned to its agent. 2. Add many unrelated tasks and pending questions to the company. 3. Open the chat from a fresh application cache. 4. Compare recent-comment arrival with the pending-question response and content reveal. **Paperclip version or commit** Baseline: `909e29dd071b1aeeb24c2933af049da90a6066d3`. Its affected services match the observed hosted revision `4eaa435bf4`. ## What Changed - Add an internal task-question projection to the attention service. Filter pending interactions by company, task IDs and question kind before card enrichment. - Keep the same access, audience, dismissal, queue, snooze, retention, archive and training-example logic. Ranks are local to the returned question list. - Use the projection from the conversation receipt service. Keep current chat audience and session checks there. - Batch seeded membership inserts in groups of 500. Keep the queue lock, conflict protection, audit events and activity logging for each new membership. Existing members produce no new audit records. - Add real PostgreSQL regression cases and a reproducible paired benchmark. No schema migration or UI reveal change is needed. ## Verification - `pnpm -r typecheck` passed. The final server typecheck also passed after the queue change. - `pnpm build` passed. - Real PostgreSQL service coverage: 57 attention and chat-handoff tests passed. Seven queue-route tests passed, including concurrent reads, mixed existing/new items, duplicates, disabled seeds and audit preservation. - Red/green proof: the unrelated-attention regression fails with the baseline conversation implementation and passes with the scoped read. - `node scripts/check-module-boundaries.mjs` and `git diff --check` passed. - Full `pnpm test:run` was attempted and stopped with exit 130 after embedded PostgreSQL startup failures and 17 failures in the untouched native-session executor suite. It is not a local pass. The focused Docker/PostgreSQL results above completed before Docker Desktop became unavailable. A direct native PostgreSQL probe identified the host semaphore limit (`could not create semaphores: No space left on device`). No shared kernel settings or other test clusters were changed. [Full CI](https://github.com/paperclipai/paperclip/actions/runs/41162314995) passed on `2809f096b3fb2c01b44a96a1b82a27809c9359df`, including all eight browser shards. Final status: 55 successful checks/statuses, three skipped and one neutral. Greptile is 5/5 with no findings or unresolved threads. The fresh local browser retest is blocked because Docker Desktop cannot start and native PostgreSQL cannot allocate semaphores. The original hosted reproduction above is complete; no candidate browser pass is claimed. Local service benchmark: PostgreSQL 17.11, two relevant tasks, five alternating pairs per scenario, after warmup. These are local service timings, not a claim about deployed latency. | Fixture | Read | Baseline median (range) | Candidate median (range) | SQL calls | | --- | --- | --- | --- | --- | | 1,000 unrelated tasks/questions | Chat questions | 670 ms (632–1,905) | 12 ms (11–15) | 1,076 → 22 | | 1,000 unrelated tasks/questions | Company badge summary | 641 ms (622–717) | 167 ms (161–171) | 1,068 → 69 | | Small company | Chat questions | 38 ms (37–52) | 13 ms (12–16) | 52 → 22 | | Small company | Company badge summary | 34 ms (33–39) | 34 ms (32–40) | 44 → 43 | All question fields and ordering matched, except rank is relative to the scoped list. Summary fields matched except the generation timestamp. The interaction plan changed from 1,002 selected rows to two rows through the existing company/issue/status index. The benchmark loads baseline attention, conversation and queue modules together so the queue change cannot contaminate the baseline. ```sh pnpm --filter @paperclipai/server exec tsx ../scripts/benchmark-chat-questions.ts \ --baseline-ref=909e29dd07 --unrelated=1000 ``` ## Risks - Scoped and complete feeds must share policy. This change reuses the same attention collection and finalization path and tests dismissals, named audiences, snoozing, archives and private access. - Batched inserts must audit only new members. The concurrent PostgreSQL test checks unique membership and one event/activity record per new item across batch boundaries. - Full inbox summaries still collect the company feed. The small-company summary timing is unchanged. Other chat requests and transcript hydration can still contribute to hosted latency. - The first reveal still waits for question cards to preserve layout. This follow-up has not been deployed, so its hosted effect remains unverified. ## Model Used OpenAI Codex, based on GPT-6, with reasoning, repository tools, code execution and browser profiling. The exact serving model ID and context-window size are not exposed in this session. ## Checklist - [x] I have included a thinking path that traces from project context to this change - [x] I have specified the model used (with version and capability details) - [x] I have checked ROADMAP.md and confirmed this PR does not duplicate planned core work - [x] I have searched GitHub for duplicate or related PRs and linked them above - [x] I have either (a) linked existing issues with `Fixes: #` / `Closes #` OR (b) described the issue in-PR following the relevant issue template - [x] I have not referenced internal/instance-local Paperclip issues or links (only public GitHub `#NNN` / `github.com/paperclipai/paperclip` URLs) - [x] My branch name describes the change (e.g. `docs/...`, `fix/...`) and contains no internal Paperclip ticket id or instance-derived details - [x] I have run tests locally and they pass - [x] I have added or updated tests where applicable - [x] I have updated relevant documentation to reflect my changes - [x] I have considered and documented any risks above - [x] All Paperclip CI gates are green - [x] Greptile is 5/5 with no open P2s, recommendations, or follow-ups - [x] I will address all Greptile and reviewer comments before requesting merge Co-authored-by: Paperclip <noreply@paperclip.ing>