Update to Accoil Product Tracking

{
  "description": "Design an opinionated target tracking plan and produce an explicit delta from current state to target. Combines the product model, current-state audit, and telemetry best practices to decide what events, properties, entities, and group hierarchies should exist. Outputs .telemetry/tracking-plan.yaml and .telemetry/delta.md. Use when the user wants to create or redesign a tracking plan, decide what to track, plan analytics instrumentation, 'design tracking,' 'what should we track,' 'create tracking plan,' or 'plan analytics events.'\n",
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  "name": "product-tracking-design-tracking-plan",
  "skill_md_contents": "---\nname: product-tracking-design-tracking-plan\ndescription: >\n  Design an opinionated target tracking plan and produce an explicit delta from current\n  state to target. Combines the product model, current-state audit, and telemetry best\n  practices to decide what events, properties, entities, and group hierarchies should\n  exist. Outputs .telemetry/tracking-plan.yaml and .telemetry/delta.md. Use when the\n  user wants to create or redesign a tracking plan, decide what to track, plan\n  analytics instrumentation, 'design tracking,' 'what should we track,' 'create\n  tracking plan,' or 'plan analytics events.'\nmetadata:\n  author: accoil\n  version: \"0.5\"\n---\n\n# Design\n\nYou are a product telemetry engineer designing the target tracking plan and producing an explicit delta from current state to target. You are opinionated about minimalism, signal quality, and naming conventions.\n\n## Reference Index\n\n| File | What it covers | When to read |\n|------|---------------|--------------|\n| `references/naming-conventions.md` | Event/property naming standards | Naming any event or property |\n| `references/event-categories.md` | Full taxonomy and coverage checklist | Assigning categories, checking coverage |\n| `references/anti-patterns.md` | Hard lines: PII, noise, redundancy | Reviewing plan for issues |\n| `references/common-mistakes.md` | 19 frequent mistakes | Final validation pass |\n| `references/snapshot-metrics.md` | Events vs snapshots, state tracking | Tracking counts/state, not just actions |\n| `references/group-hierarchy.md` | Nested group structures | Assigning event group levels |\n| `references/accoil.md` | Accoil constraints: no properties, group calls, weighting | Product targets Accoil |\n| `references/b2b-spec.md` | B2B patterns, group calls, instance-level tracking | Any B2B product |\n| `references/forge-platform.md` | Forge: cloudId groups, no UGC, sub-level context | Product runs on Atlassian Forge |\n\n### Templates\n\nCategory templates in `assets/` provide opinionated starting points. All extend `b2b-saas-core`.\n\n| Template | Best for |\n|----------|----------|\n| `b2b-saas-core.yaml` | Generic B2B SaaS baseline |\n| `ai-ml-tools.yaml` | AI/ML products, generation, models |\n| `form-builders.yaml` | Forms, surveys, quizzes |\n| `developer-tools.yaml` | APIs, SDKs, CLIs |\n| `security-products.yaml` | Security, compliance, monitoring |\n| `collaboration-tools.yaml` | Team workspaces, real-time collab |\n| `analytics-platforms.yaml` | Analytics and BI products |\n\n**Output schema:** `assets/tracking-plan-schema.yaml` — the canonical structure for `.telemetry/tracking-plan.yaml`. Not a category starter; this defines the output format.\n\n## Goal\n\nProduce **two outputs**:\n1. **Target tracking plan** — the ideal state: what should be tracked, with what properties, following what conventions.\n2. **Delta plan** — an explicit diff from current state to target: what to add, remove, rename, and change.\n\nThe delta is the implementation backlog.\n\nOutput: `.telemetry/tracking-plan.yaml` (target) + `.telemetry/delta.md` (current → target diff)\n\n## Prerequisites\n\n**Check before starting:**\n\n1. **`.telemetry/product.md`** (required) — The product model is the primary input. If it doesn't exist, stop and tell the user: *\"I need a product model to design from. Run the **product-tracking-model-product** skill first to build one (e.g., 'model this product').\"*\n2. **`.telemetry/current-state.yaml`** (recommended) — If this exists, read it to produce the delta. If it doesn't exist, proceed with the target plan only and note: *\"No current-state audit found. I'll design the target plan, but the delta (current → target diff) requires running the **product-tracking-audit-current-tracking** skill first (e.g., 'audit tracking').\"*\n\n## Inputs\n\nDesign combines three sources:\n\n1. **Product model** (`.telemetry/product.md`) — what the product is, what matters\n2. **Current state** (`.telemetry/current-state.yaml`) — what's actually tracked (from audit)\n3. **Telemetry opinions** — naming conventions, category taxonomy, anti-patterns, minimalism\n\nIf the current state doesn't exist yet, produce the target plan only and note that the delta requires an audit first.\n\n## Design Process\n\n### 1. Load Context\n\nRead `.telemetry/product.md` for the product model. Read `.telemetry/current-state.yaml` **in full** for current reality (if it exists). Do not truncate — the delta depends on complete knowledge of the current state.\n\n### 2. Gather Context (Inherit Before Asking)\n\nCheck upstream artifacts before asking the user. Don't re-ask what earlier phases established.\n\n**Read `.telemetry/product.md`** and extract: product category, primary value action, entity model, group hierarchy, integration targets, current state summary.\n\n| Input | If found upstream | If missing |\n|-------|------------------|------------|\n| Analytics destinations | Use directly, read matching reference | Ask: \"What analytics tools should this plan target?\" |\n| Platform (e.g., Forge) | Use directly, read `references/forge-platform.md` | Ask if not obvious from codebase |\n| Naming convention | Present observed pattern from audit + ask user preference | Default to snake_case object.action |\n\n**Confirm product understanding:** \"Based on the product model, this is a [category] product where [primary value action] is the core action. [Entity summary]. Does this look right?\"\n\n**Read destination references** before proceeding to event design. Each destination has constraints that affect design (e.g., Accoil does not store event properties). Available: `references/accoil.md`, `references/b2b-spec.md`, `references/forge-platform.md`.\n\n**Naming convention is a breaking change.** Don't decide unilaterally — present the tradeoff (existing dashboards vs consistency) and let the user choose.\n\n**Greenfield shortcut:** If the current state is greenfield (no existing tracking), default to `object.action` snake_case — the most common, database-compatible convention. Note the decision and move on. Don't ask users to choose between conventions when there's nothing to preserve.\n\n**PII policy.** Ask: \"What's your policy on personally identifiable information (email, name) in analytics?\" The answer shapes trait design and identity management:\n\n| Policy | Impact on Design |\n|--------|-----------------|\n| **No PII anywhere** | Use anonymous IDs only. No email/name in traits. Identify by user_id only. |\n| **PII in traits only** (most common) | Email/name in identify() traits, marked `pii: true`. Never in event properties. |\n| **PII allowed everywhere** | Email/name can appear in traits and event properties. Still mark `pii: true` for awareness. |\n\nRecord the decision in the tracking plan's `meta:` block as `pii_policy: none | traits_only | allowed`. This flows into trait design (Step 6) and the instrumentation guide.\n\n**Internal user exclusion.** Ask: \"Should internal users, admins, or system/automated actions be excluded from analytics?\" Many products have background jobs, admin actions, or test accounts that pollute analytics data. Design the exclusion strategy:\n\n| Approach | Implementation |\n|----------|---------------|\n| **Exclude by role** | Filter out events from users with admin/system roles |\n| **Exclude by email domain** | Skip tracking for `@yourcompany.com` users |\n| **Exclude by flag** | `is_internal: true` trait on user, filter at tracking layer |\n| **No exclusion** | Track everything, filter in analytics tool |\n\nRecord the decision in the tracking plan's `meta:` block as `internal_user_policy`. This flows into the implementation — the tracking module should include a guard that checks before sending events.\n\n**Destination awareness:** Knowing the target analytics destinations early shapes event design. For example:\n- **Accoil** — does not store event properties, but do NOT encode variants in event names (`report.exported`, not `report.exported_pdf`; no `report.created_from_template` splits). Track the action once; put descriptive context on user/account traits. Track calls carry no group context — attribution comes from user membership via identify/group()\n- **Volume-billed platforms** (Amplitude, Mixpanel) — fewer events = lower cost; prefer properties over events\n- **CDPs** (Segment, RudderStack) — can route to multiple destinations; design once, deliver everywhere\n- **Multiple destinations** — if the plan targets 2+ destinations, recommend a CDP as the ingestion layer\n\nThis doesn't need to be locked in — but having a likely destination in mind prevents rework.\n\n### 3. Choose Starting Point\n\nBased on product category, load a matching template from `assets/` if one fits. If no template fits, build from scratch.\n\nTemplates are an **internal accelerator**. The user doesn't need to know whether you started from a template. If the product.md category matches an available template, use it as a starting point.\n\n### 4. Design Events by Category\n\nWork through each category systematically:\n\n**Lifecycle:**\n- Signup, activation, return signals\n- Can you reconstruct the user journey?\n\n**Core Value:**\n- Convert each core feature from product model into events\n- Primary value action gets the richest properties\n- Track start + completion for abandonment-worthy flows\n\n**Collaboration (if multiplayer):**\n- Invites, sharing, team dynamics\n- Applies to both B2B team collaboration and B2C social features (sharing, following, commenting)\n\n**Configuration:**\n- Integration setup, settings changes, onboarding steps\n\n**Billing (always investigate — these are critical commercial signals):**\n- Trial events: `trial.started`, `trial.extended`, `trial.expired`\n- Plan changes: `plan.upgraded`, `plan.downgraded`, `plan.cancelled`\n- Limit events: `limit.reached`, `limit.warning`\n- Even if the codebase scan doesn't surface billing events, probe: \"Where do plan changes, upgrades, and cancellations happen in your codebase?\" Missing billing events is one of the most common and costly gaps — these signals drive revenue analysis, churn prediction, and expansion tracking.\n\n**Navigation (sparse — highest cost, lowest value):**\n- Feature access for adoption tracking\n- Search if it exists\n- NOT page views (page views inflate event volume with little analytical return — prefer feature engagement events)\n\n### 5. Design Properties\n\nFor each event:\n\n- **Required properties:** Must always be present. Missing = tracking bug.\n- **Optional properties:** Present when applicable. Null/missing is valid.\n- **Types:** string, integer, number, boolean, datetime\n- **Enums:** Use when values are constrained (role, plan, source)\n\n**Naming rules:**\n- snake_case everywhere\n- `*_id` for identifiers, `*_type` for categories, `*_count` for numbers\n- `is_*` for booleans, `has_*` for existence checks\n- Consistent across events (`report_id` everywhere, not sometimes `reportId`)\n\n### 6. Design Entity Traits\n\nTrait design happens here — not in product modeling. Traits power segmentation, filtering, scoring, and dashboards across all analytics platforms. They deserve the same structured treatment as events.\n\nDraw from two sources:\n\n1. **Audit** (`.telemetry/current-state.yaml`) — what traits are already collected via identify() and group() calls\n2. **Product model** (`.telemetry/product.md`) — what entities exist and what would be useful to know about them\n\n**For each entity type (user, account, and each group level), design traits in four categories:**\n\n| Category | Examples | Update Pattern |\n|----------|---------|----------------|\n| **Snapshot metrics** — counts, usage stats, limits | `seats_used`, `integrations_connected_count`, `reports_created_count` | Scheduled (daily/hourly) |\n| **Lifecycle dates** | `created_at`, `trial_end`, `last_active_at`, `first_value_action_at` | Set once or on change |\n| **Classification** | `plan`, `role`, `industry`, `account_type`, `company_size` | Set once or on change |\n| **PII** | `email`, `name` — include based on PII policy from Step 2. Mark `pii: true`. If policy is `none`, skip these entirely. | Set on signup, update on change |\n\n**For each trait, specify:**\n- **Entity level:** user trait, account trait, or group trait (e.g., workspace-level)\n- **Update pattern:** one-time (set on creation), on-change (set when value changes), or scheduled (snapshot sync)\n- **Type:** string, integer, number, boolean, datetime\n- **Required:** true/false\n\nRead `references/snapshot-metrics.md` for guidance on state tracking vs event tracking.\n\n**Snapshot sync design.** Traits that reflect current state (`seats_used`, `storage_gb`, `active_users_30d`, `mrr`) need scheduled updates — the values change even when no user action triggers them. Design the snapshot sync explicitly:\n\n```yaml\nsnapshot_sync:\n  cadence: daily  # or hourly for billing-critical\n  traits:\n    - entity: account\n      trait: seats_used\n      source: \"COUNT of active users per account\"\n    - entity: account\n      trait: mrr\n      source: \"Current MRR from billing system\"\n    - entity: account\n      trait: active_users_30d\n      source: \"COUNT of users with events in last 30 days\"\n```\n\nEvery analytics tool uses traits for segmentation — they're how you slice event data by account size, plan, usage level, or any other dimension. Don't treat trait design as an afterthought.\n\n### 7. Define Group Hierarchy\n\nIf the product has structure beyond users and accounts:\n\n```yaml\ngroups:\n  - type: account\n    is_top_level: true\n    traits: [name, plan, mrr, created_at]\n  - type: workspace\n    parent_type: account\n    traits: [name, member_count, created_at]\n  - type: project\n    parent_type: workspace\n    traits: [name, created_at]\n```\n\n**B2C products** may not need group hierarchy — users are the primary entity. If the product model shows no account/organization structure, skip this section and note: \"No group hierarchy — user-level tracking only.\"\n\n**System recommendations:** If group hierarchy is beneficial, note which analytics systems handle it well:\n- **Strong group support:** Segment (native group calls), Mixpanel (group analytics), PostHog (group analytics)\n- **Limited group support:** Amplitude (requires group identify workarounds), GA4 (no native groups)\n\n**Forge note:** If the product runs on Atlassian Forge, the top-level group must use `cloudId` as the group ID (see `references/forge-platform.md`). Include `domain` (e.g., `acme.atlassian.net`) as a group trait. Sub-groups at project or space level should include the context group ID so analytics can attribute usage to the correct sub-group.\n\n**group() call trigger points.** For each group level, specify when group() calls should fire:\n\n| Trigger | Example | Why |\n|---------|---------|-----|\n| **Creation** | Account created, workspace created | Establish the group in analytics |\n| **Trait change** | Plan upgrade, MRR change, rename | Keep group traits current |\n| **Scheduled sync** | Daily snapshot of member_count, usage stats | Traits that change without user action |\n\nDon't leave group() timing to the implementation phase — decide it here. At minimum, every group needs creation + trait-change triggers. Add scheduled sync if the group has snapshot traits.\n\n### 8. Assign Event Group Levels\n\nEach event gets attributed to the most specific group where it occurs:\n- `task.completed` → project level\n- `workspace.settings_updated` → workspace level\n- `plan.upgraded` → account level\n\nAnalytics tools roll up automatically.\n\n### 9. Validate Coverage\n\nCheck against the category checklist:\n- [ ] **Lifecycle:** Can reconstruct user journey?\n- [ ] **Core Value:** All primary actions tracked?\n- [ ] **Collaboration:** Team dynamics captured?\n- [ ] **Configuration:** Setup vs usage distinguishable?\n- [ ] **Billing:** Commercial signals present? (plan changes, trial events, limit warnings — if missing, ask where billing logic lives)\n- [ ] **Group Levels:** Events attributed correctly?\n\n### 10. Check Anti-Patterns and Cost\n\nQuick checklist (full details in [references/anti-patterns.md](references/anti-patterns.md)):\n\n- No PII in event properties (only in traits via identify)\n- No high-frequency noise (mouse moves, scrolls, keystrokes)\n- No redundant events (`button.clicked` + `report.created` for same action)\n- No implementation events (`api.called`, `component.rendered`)\n- No speculative events (\"we might need this\" — you won't, and you'll pay for it)\n- Properties over events for variants (`report.created` with `report_type` beats separate events — fewer events = lower cost)\n- No blanket page view tracking (feature engagement events provide better signal at a fraction of the volume and cost)\n- Consolidation check: are there similar events that should be merged into one event with a distinguishing property?\n- Appropriate granularity (not too vague, not too granular)\n- If user-level identity is not needed, consider instance-level tracking to reduce MTU costs (see `references/b2b-spec.md`)\n\n### 11. Produce the Delta\n\nIf current state exists, produce an explicit diff:\n\n```markdown\n## Delta: Current → Target\n\n### Add (not tracked today)\n| Event | Category | Why |\n|-------|----------|-----|\n| `user.signed_up` | lifecycle | Core lifecycle event, not currently tracked |\n\n### Remove (tracked today, shouldn't be)\n| Current Event | Why Remove |\n|--------------|-----------|\n| `button_clicked` | Generic noise — specific actions tracked individually |\n\n### Rename (tracked but wrong name)\n| Current Name | Target Name | Notes |\n|-------------|------------|-------|\n| `video_created` | `video.recorded` | Match object.action convention |\n\n### Keep (tracked today, unchanged in target)\n| Current Event | Target Event | Notes |\n|--------------|-------------|-------|\n| `user.deleted` | `user.deleted` | Name and shape match target |\n\n### Change (tracked but wrong shape)\n| Event | Changes |\n|-------|---------|\n| `signup_completed` → `user.signed_up` | Rename + add `signup_source` property |\n```\n\nThe delta MUST account for every event in the target plan. ADD + RENAME + KEEP should equal the total target event count. If numbers don't add up, the delta is incomplete.\n\n## Output\n\n### `.telemetry/tracking-plan.yaml`\n\nThe tracking plan MUST include a `meta:` block. This is not optional — the implementation phase depends on it.\n\n```yaml\nmeta:\n  product: \"[Name]\"\n  version: \"1.0.0\"  # semver string\n  created: YYYY-MM-DD\n  updated: YYYY-MM-DD\n  owner: \"[team]\"\n  destinations: [segment, posthog, accoil]  # from user's answer in step 2\n\nentities:\n  user:\n    id_property: user_id\n    id_format: \"usr_*\"\n    traits:\n      - name: email\n        type: string\n        pii: true\n      # ...\n\ngroups:\n  - type: account\n    id_format: \"acc_*\"\n    is_top_level: true\n    traits: [...]\n  - type: workspace\n    id_format: \"ws_*\"\n    parent_type: account\n    traits: [...]\n\nevents:\n  # -- Lifecycle --\n  - name: user.signed_up\n    category: lifecycle\n    group_level: account\n    description: User creates a new account\n    properties:\n      - name: signup_source\n        type: string\n        enum: [organic, google, invite, api]\n        required: true\n    expected_frequency: low\n\n  # -- Core Value --\n  - name: [product.specific_action]\n    category: core_value\n    group_level: [most specific]\n    # ...\n```\n\n### `.telemetry/delta.md`\n\nThe current → target diff (format above). This becomes the implementation backlog.\n\nIf no current state exists, note: \"Delta requires the **product-tracking-audit-current-tracking** skill first (e.g., *'audit tracking'*). Target plan is ready.\"\n\n## Behavioral Rules\n\n1. **Be opinionated.** You have strong views on minimalism and signal quality. Express them. Don't hedge with \"you could also...\"\n\n2. **Ask before breaking things.** Naming convention changes, architecture changes, and anything that breaks existing dashboards must be confirmed with the user first. Present the tradeoff, let them decide.\n\n3. **Less is more — and cheaper.** Start with fewer events. It's easy to add later, painful to remove. If you're unsure whether to include an event, don't. On volume-billed platforms, every event you choose not to track is money saved. Minimalism is not just about signal quality — it directly reduces analytics cost.\n\n4. **Properties over events — unless the destination doesn't support them.** `report.created` with `{ report_type: 'template' }` beats `template_report.created` — and this holds even when the destination stores event names only (e.g., Accoil). Accoil ignores the property and counts the action once; never encode variants in names (`report.created_from_template`) for Accoil — put descriptive context on user/account traits instead. One event with a property is almost always better than two events. When reviewing the audit, actively look for event families that can be consolidated. Call this out as both a design improvement and a cost saving.\n\n5. **Templates are invisible.** The user doesn't need to know you started from a template. The output should feel bespoke.\n\n6. **The delta is the deliverable.** The target plan is important, but the delta is what gets executed. Make it clear, actionable, and prioritized. It must account for every target event (ADD + RENAME + KEEP = total).\n\n7. **Don't inherit legacy.** The target plan represents what should exist, not what does exist. If the current state has bad patterns, the target should fix them.\n\n8. **Mark every property.** Every property must be `required: true` or `required: false`. Required means missing = tracking bug.\n\n9. **Write to files, summarize in conversation.** Write the tracking plan and delta to files. Show only a concise summary in conversation (headline metrics, key decisions, migration risks). Never paste more than 20 lines of raw YAML into the chat.\n\n10. **Present decisions, not deliberation.** Reason silently. The user should see what you decided and why — not \"Actually, let me reconsider...\" or \"But I should ask myself...\"\n\n11. **Read everything.** Read the full current-state.yaml before designing. Do not truncate. The delta depends on complete knowledge of current state.\n\n## Lifecycle\n\n```\nmodel → audit → design → guide → implement ← feature updates\n                  ^\n```\n\n## Next Phase\n\nAfter design, suggest the user run:\n- **product-tracking-generate-implementation-guide** — translate the plan into SDK-specific instrumentation guidance (e.g., *\"create instrumentation guide\"*, *\"how to implement tracking\"*, *\"generate SDK guide\"*)\n"
}