Linear Cleanup Taxonomy — Naming and Labels
Purpose: Single source of truth for how Linear initiatives, projects, and labels should look when aligning to the Brainforge service line → subservice → offering model. Use for full cleanup, kickoffs, and ongoing consistency.
Scope: Applies to the entire workspace — all client teams and all internal teams, not just LMNT. Use this taxonomy for every team when running cleanup or audits.
References: README.md, linear-api-setup.md, linear-board-audit-sop.md. Discovery: linear-full-cleanup-discovery-report-2026-03-17.md.
1. Team list (client vs internal) and hierarchy
Maintain in knowledge/sales/linear-teams-client-internal.md (see that file for the canonical list). Summary:
- Client teams: LMNT, CTA, Eden, EdenOS, MinuteMD-Amble, Magicspoon, Hedra, Interlude Studio, ABC Home and Commercial, ABC Team, GlobalVetLink, Urban Stems, Lilo Social, Insomnia Cookies, Ellie Mental Health, Honey Stinger, Rimo, Hyp+Access, iCustomer, SME Playbooks/Testimonials.
- Internal teams: Platform, Delivery, GTM, Sales, Marketing, Operations, Finance, Legal, Recruitment, Onboarding & Offboarding, Project Management, Content, Management, Exec, Sick/OOO Request, Default, TEST, TEST2, ARCHIVE.
Sub-team hierarchy (configure in Linear: Settings → Teams → Team hierarchy):
- Operations → sub-teams: Sick/ OOO Request, Onboarding & Offboarding
- Sales → sub-teams: GTM, Content
Use this to run cleanup in order: internal first, then client teams one by one.
2. Initiative naming
| Context | Pattern | Example |
|---|---|---|
| Client workstream | Client | Workstream | LMNT | Data Modeling, LMNT | Ingestion, Amble | Phase 0 |
| Internal — service line | Service line name | Data, AI, Strategy & Analytics (or “Data Service”, “A.I Service”, “Strategy Service” if already used) |
| Internal — workstream | Area — Workstream | Platform — Reliability, Q2 2026 Platform Planning |
| Offering-level (cross-team) | Offering - Service or offering name | Edge-to-Activation - Service |
Initiatives map to service line (Data / AI / Strategy & Analytics) for internal; for client, initiatives map to SOW/roadmap workstreams (e.g. Option B: Ingestion, Data Modeling, Reporting and Analytics, Documentation, Adoption, VP Level Strategy).
3. Project naming
| Context | Pattern | Example |
|---|---|---|
| Canonical (template) | {Line} — {Offering} (Canonical) | Data — dbt Audit (Canonical) |
| Client engagement | [Client] {Offering} or per implementation plan | [Client] Omni Zero-to-One, LMNT | Wholesale Data Mart |
| Internal | Offering or workstream name | Data Platform, GTM Campaign Briefs |
Align to README.md naming conventions. Folder slug = kebab-case; Linear project name = title case as in table.
4. Labels (standard set)
Use these for filtering and alignment across teams.
| Category | Label names | When to use |
|---|---|---|
| Service line | data, ai, strategy-analytics | Every issue/project that belongs to that line |
| Subservice | data-platform, data-modeling, reverse-etl, data-strategy, measurement-kpis, reporting-insights, workflow-automation, knowledge-engineering, copilots-agents (see table below) | One primary subservice label when work maps to a bucket; optional but recommended for SL views. reverse-etl = Reverse ETL (proposal — services README Decision 6). |
| Phase | phase-0, phase-1, phase-2 | Option B / implementation plan phase (prefer lowercase kebab). Alternative: “Phase 0”, “Phase 1”, “Phase 2” if org already uses that. |
| Offering / engagement | omni, edge-to-activation, dbt-audit, full-data-platform, etc. | Match vault folder slug or offering name |
| Operational | ai-assignable, human-only | Per linear-labels-ai-human.md |
| Delivery | client-dependency, internal | Blocked on client action vs internal Brainforge task (from omni linear-template) |
Create missing org/team labels in Linear when running cleanup. Do not remove existing capability labels (cap-, ops-) unless consolidating; add the standard set above for consistency.
Subservice (issue labels — canonical kebab slugs)
Use one primary subservice label on in-scope engineering issues when work maps to a subservice. Canonical names match the taxonomy pilot and cross-client views (apps/platform/scripts/create-linear-views-bulk.ts).
| Line | Display name | Linear label (canonical) |
|---|---|---|
| Data | Data Platform | data-platform |
| Data | Data Modeling | data-modeling |
| Data | Reverse ETL | reverse-etl |
| Strategy & Analytics | Data Strategy | data-strategy |
| Strategy & Analytics | Measurement & KPIs | measurement-kpis |
| Strategy & Analytics | Reporting & Insights | reporting-insights |
| AI | Workflow Automation | workflow-automation |
| AI | Knowledge Engineering | knowledge-engineering |
| AI | Copilots & Agents | copilots-agents |
Legacy labels (still on older issues until relabeled): data-infrastructure → treat as Data Platform; analytics-bi → Data Modeling; metrics-kpis → Measurement & KPIs; ai-infrastructure → Copilots & Agents. Audits and the taxonomy pilot normalize these to the canonical slugs above.
Vault folder paths may still use older directory names (data-infrastructure/, analytics-bi/, etc.); that is separate from Linear label strings — see README.md.
5. Order of operations for cleanup
-
Discovery — List teams, initiatives, projects, issues (no project), labels → discovery report.
-
Taxonomy — This doc + team list in vault.
-
Structure — Per team: align initiatives and projects to this taxonomy; link projects to initiatives; archive/merge duplicates.
-
Tickets — Per team: assign issues to projects (linear-structure-hygiene Appendix A, or alias linear-tickets-to-projects); SOW alignment for clients; apply labels; optional board audit and status sync.
-
Workflow states (statuses) — Per client team: align issue statuses to a standard set so boards and views are consistent. Audit: run
apps/platform/scripts/audit-linear-workflow-states.tsto list each client team’s workflow states. Guideline: linear-status-cleanup.md — recommended state names, variant → standard mapping, and cleanup steps (rename/merge in Linear UI).
Always run audit-only before apply; confirm before bulk writes.