Files
paperclip/server/src/__tests__/company-skills-service.test.ts
T
Dotta 5f45712846 Sync/master post pap1497 followups 2026 04 15 (#3779)
## Thinking Path

> - Paperclip orchestrates AI agents for zero-human companies
> - The board depends on issue, inbox, cost, and company-skill surfaces
to stay accurate and fast while agents are actively working
> - The PAP-1497 follow-up branch exposed a few rough edges in those
surfaces: stale active-run state on completed issues, missing creator
filters, oversized issue payload scans, and placeholder issue-route
parsing
> - Those gaps make the control plane harder to trust because operators
can see misleading run state, miss the right subset of work, or pay
extra query/render cost on large issue records
> - This pull request tightens those follow-ups across server and UI
code, and adds regression coverage for the affected paths
> - The benefit is a more reliable issue workflow, safer high-volume
cost aggregation, and clearer board/operator navigation

## What Changed

- Added the `v2026.415.0` release changelog entry.
- Fixed stale issue-run presentation after completion and reused the
shared issue-path parser so literal route placeholders no longer become
issue links.
- Added creator filters to the Issues page and Inbox, including
persisted filter-state normalization and regression coverage.
- Bounded issue detail/list project-mention scans and trimmed large
issue-list payload fields to keep issue reads lighter.
- Hardened company-skill list projection and cost/finance aggregation so
large markdown blobs and large summed values do not leak into list
responses or overflow 32-bit casts.
- Added targeted server/UI regression tests for company skills,
costs/finance, issue mention scanning, creator filters, inbox
normalization, and issue reference parsing.

## Verification

- `pnpm exec vitest run
server/src/__tests__/company-skills-service.test.ts
server/src/__tests__/costs-service.test.ts
server/src/__tests__/issues-goal-context-routes.test.ts
server/src/__tests__/issues-service.test.ts ui/src/lib/inbox.test.ts
ui/src/lib/issue-filters.test.ts ui/src/lib/issue-reference.test.ts`
- `gh pr checks 3779`
Current pass set on the PR head: `policy`, `verify`, `e2e`,
`security/snyk (cryppadotta)`, `Greptile Review`

## Risks

- Creator filter options are derived from the currently loaded
issue/agent data, so very sparse result sets may not surface every
historical creator until they appear in the active dataset.
- Cost/finance aggregate casts now use `double precision`; that removes
the current overflow risk, but future schema changes should keep
large-value aggregation behavior under review.
- Issue detail mention scanning now skips comment-body scans on the
detail route, so any consumer that relied on comment-only project
mentions there would need to fetch them separately.

## Model Used

- OpenAI Codex, GPT-5-based coding agent with terminal tool use and
local code execution in the Paperclip workspace. Exact internal model
ID/context-window exposure is not surfaced 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 run tests locally and they pass
- [x] I have added or updated tests where applicable
- [ ] If this change affects the UI, I have included before/after
screenshots
- [x] I have updated relevant documentation to reflect my changes
- [x] I have considered and documented any risks above
- [x] I will address all Greptile and reviewer comments before
requesting merge

---------

Co-authored-by: Paperclip <noreply@paperclip.ing>
2026-04-15 21:13:56 -05:00

93 lines
3.2 KiB
TypeScript

import { randomUUID } from "node:crypto";
import os from "node:os";
import path from "node:path";
import { promises as fs } from "node:fs";
import { afterAll, afterEach, beforeAll, describe, expect, it } from "vitest";
import { companies, companySkills, createDb } from "@paperclipai/db";
import {
getEmbeddedPostgresTestSupport,
startEmbeddedPostgresTestDatabase,
} from "./helpers/embedded-postgres.js";
import { companySkillService } from "../services/company-skills.ts";
const embeddedPostgresSupport = await getEmbeddedPostgresTestSupport();
const describeEmbeddedPostgres = embeddedPostgresSupport.supported ? describe : describe.skip;
if (!embeddedPostgresSupport.supported) {
console.warn(
`Skipping embedded Postgres company skill service tests on this host: ${embeddedPostgresSupport.reason ?? "unsupported environment"}`,
);
}
describeEmbeddedPostgres("companySkillService.list", () => {
let db!: ReturnType<typeof createDb>;
let svc!: ReturnType<typeof companySkillService>;
let tempDb: Awaited<ReturnType<typeof startEmbeddedPostgresTestDatabase>> | null = null;
const cleanupDirs = new Set<string>();
beforeAll(async () => {
tempDb = await startEmbeddedPostgresTestDatabase("paperclip-company-skills-service-");
db = createDb(tempDb.connectionString);
svc = companySkillService(db);
}, 20_000);
afterEach(async () => {
await db.delete(companySkills);
await db.delete(companies);
await Promise.all(Array.from(cleanupDirs, (dir) => fs.rm(dir, { recursive: true, force: true })));
cleanupDirs.clear();
});
afterAll(async () => {
await tempDb?.cleanup();
});
it("lists skills without exposing markdown content", async () => {
const companyId = randomUUID();
const skillId = randomUUID();
const skillDir = await fs.mkdtemp(path.join(os.tmpdir(), "paperclip-heavy-skill-"));
cleanupDirs.add(skillDir);
await fs.writeFile(path.join(skillDir, "SKILL.md"), "# Heavy Skill\n", "utf8");
await db.insert(companies).values({
id: companyId,
name: "Paperclip",
issuePrefix: `T${companyId.replace(/-/g, "").slice(0, 6).toUpperCase()}`,
requireBoardApprovalForNewAgents: false,
});
await db.insert(companySkills).values({
id: skillId,
companyId,
key: `company/${companyId}/heavy-skill`,
slug: "heavy-skill",
name: "Heavy Skill",
description: "Large skill used for list projection regression coverage.",
markdown: `# Heavy Skill\n\n${"x".repeat(250_000)}`,
sourceType: "local_path",
sourceLocator: skillDir,
trustLevel: "markdown_only",
compatibility: "compatible",
fileInventory: [{ path: "SKILL.md", kind: "skill" }],
metadata: { sourceKind: "local_path" },
});
const listed = await svc.list(companyId);
const skill = listed.find((entry) => entry.id === skillId);
expect(skill).toBeDefined();
expect(skill).not.toHaveProperty("markdown");
expect(skill).toMatchObject({
id: skillId,
key: `company/${companyId}/heavy-skill`,
slug: "heavy-skill",
name: "Heavy Skill",
sourceType: "local_path",
sourceLocator: skillDir,
attachedAgentCount: 0,
sourceBadge: "local",
editable: true,
});
});
});