GearBox/.planning/research/PITFALLS.md

# Pitfalls Research

**Domain:** Adding search/filter, weight classification, weight distribution charts, candidate status tracking, and weight unit selection to an existing gear management app (GearBox v1.2)
**Researched:** 2026-03-16
**Confidence:** HIGH (pitfalls derived from direct codebase analysis + domain-specific patterns from gear tracking community + React/SQLite ecosystem knowledge)

## Critical Pitfalls

### Pitfall 1: Weight Unit Conversion Rounding Accumulation

**What goes wrong:**
GearBox stores weight as `real("weight_grams")` (a floating-point column in SQLite). When adding unit selection (g, oz, lb, kg), the naive approach is to convert on display and let users input in their preferred unit, converting back to grams on save. The problem: repeated round-trip conversions accumulate rounding errors. A user enters `5.3 oz`, which converts to `150.253...g`, gets stored as `150.253`, then displayed back as `5.30 oz` (fine so far). But if the user opens the edit form (which shows `5.30 oz`), makes no changes, and saves, the value reconverts from the displayed `5.30` to `150.2535g` -- a different value from what was stored. Over multiple edit cycles, weights drift. More critically, the existing `SUM(items.weight_grams)` aggregates in `setup.service.ts` and `totals.service.ts` will accumulate these micro-errors across dozens of items, producing totals that visibly disagree with manual addition of displayed values. A setup showing items of "5.3 oz + 2.1 oz" but a total of "7.41 oz" (instead of 7.40 oz) erodes trust in the app's core value proposition.

**Why it happens:**
The conversion factor between grams and ounces (28.3495) is irrational enough that floating-point representation always involves truncation. Combined with SQLite's `REAL` type (8-byte IEEE 754 float, ~15 digits of precision), individual items are accurate enough, but the accumulation across conversions and summation surfaces visible errors.

**How to avoid:**
1. Store weights in grams as the canonical unit -- this is already done. Good.
2. Convert only at the display boundary (the `formatWeight` function in `lib/formatters.ts`). Never convert grams to another unit, let the user edit, and convert back.
3. When the user inputs in oz/lb/kg, convert to grams once on save and store. The edit form should always load the stored grams value and re-convert for display, never re-convert from a previously displayed value.
4. Round only at the final display step, not during storage. Use `Number(value.toFixed(1))` for display, never for the stored value.
5. For totals, compute `SUM(weight_grams)` in SQL (already done), then convert the total to display units once. Do not sum converted per-item display values.
6. Consider changing `weight_grams` from `real` to `integer` to store milligrams (or tenths of grams) for sub-gram precision without floating-point issues. This is a larger migration but eliminates the class of errors entirely.

**Warning signs:**
- Edit form pre-fills with a converted value and saves by reconverting that value
- `formatWeight` is called before summation rather than after
- Unit conversion is done in multiple places (client and server) with different rounding
- Tests compare floating-point totals with `===` instead of tolerance-based comparison

**Phase to address:**
Phase 1 (Weight unit selection) -- the conversion layer must be designed correctly from the start. Getting this wrong poisons every downstream feature (charts, setup totals, classification breakdowns).

---

### Pitfall 2: Weight Classification Stored at Wrong Level

**What goes wrong:**
Weight classification (base weight / worn / consumable) seems like a property of the item itself -- "my rain jacket is always worn weight." So the developer adds a `classification` column to the `items` table. But this is wrong: the same item can be classified differently in different setups. A rain jacket is "worn" in a summer bikepacking setup but "base weight" (packed in the bag) in a winter setup where you wear a heavier outer shell. By putting classification on the item, users cannot accurately model multiple setups with the same gear, which is the entire point of the setup feature.

**Why it happens:**
LighterPack and similar tools model classification at the list level (each list has its own classification per item), but when you look at the GearBox schema, the `setup_items` join table only has `(id, setup_id, item_id)`. It feels more natural to add a column to the item itself rather than to a join table, especially since the current `setup_items` table is minimal. The single-user context also makes it feel like "my items have fixed classifications."

**How to avoid:**
Add `classification TEXT DEFAULT 'base'` to the `setup_items` table, not to `items`. This means:
- The same item can have different classifications in different setups
- Classification is optional and defaults to "base" (the most common case)
- The `items` table stays generic -- classification is a setup-level concern
- Existing `setup_items` rows get a sensible default via the migration
- SQL aggregates for setup totals can easily group by classification: `SUM(CASE WHEN setup_items.classification = 'base' THEN items.weight_grams ELSE 0 END)`

If classification is also useful outside of setups (e.g., in the collection view for a general breakdown), add it as an optional `defaultClassification` on `items` that serves as a hint when adding items to setups, but the authoritative classification is always on `setup_items`.

**Warning signs:**
- `classification` column added to `items` table
- Setup detail view shows classification but cannot be different per setup
- Weight breakdown chart shows the same classification for an item across all setups
- No way to classify an item as "worn" in one setup and "base" in another

**Phase to address:**
Phase 2 (Weight classification) -- this is the single most important schema decision in v1.2. Getting it wrong requires migrating data out of the `items` table into `setup_items` later, which means reconciling possibly-different classifications that users already set.

---

### Pitfall 3: Search/Filter Implemented Server-Side for a Client-Side Dataset

**What goes wrong:**
The developer adds a `GET /api/items?search=tent&category=3` endpoint, sending filtered results from the server. This means:
- Every keystroke fires an API request (or requires debouncing, adding latency)
- The client's React Query cache for `["items"]` now contains different data depending on filter params, causing stale/inconsistent state
- Category grouping in `CollectionView` breaks because the full list is no longer available
- The existing `useTotals()` hook returns totals for all items, but the list shows filtered items -- a confusing mismatch

**Why it happens:**
Server-side filtering is the "correct" pattern at scale, and most tutorials teach it that way. But GearBox is a single-user app where the entire collection fits comfortably in memory. The existing `useItems()` hook already fetches all items in one call and the collection view groups them client-side.

**How to avoid:**
Implement search and filter entirely on the client side:
1. Keep `useItems()` fetching the full list (it already does)
2. Add filter state (search query, category ID) as URL search params or React state in the collection page
3. Filter the `items` array in the component using `Array.filter()` before grouping and rendering
4. The totals bar should continue to show collection totals (unfiltered), not filtered totals -- or show both ("showing 12 of 47 items")
5. Only move to server-side filtering if the collection exceeds ~500 items, which is far beyond typical for a single-user gear app

This preserves the existing caching behavior, requires zero API changes, and gives instant feedback on every keystroke.

**Warning signs:**
- New query parameters added to `GET /api/items` endpoint
- `useItems` hook accepts filter params, creating multiple cache entries
- Search input has a debounce delay
- Filtered view totals disagree with dashboard totals

**Phase to address:**
Phase 1 (Search/filter) -- the decision to filter client-side vs server-side affects where state lives and must be decided before building the UI.

---

### Pitfall 4: Candidate Status Transition Without Validation

**What goes wrong:**
The existing thread system has a simple `status: "active" | "resolved"` on threads and no status on candidates. Adding candidate status tracking (researching -> ordered -> arrived) as a simple text column without transition validation allows impossible states: a candidate marked "arrived" in a thread that was already "resolved," or a candidate going from "arrived" back to "researching." Worse, the existing `resolveThread` function in `thread.service.ts` copies candidate data to create a collection item -- but does not check or update candidate status, so a "researching" candidate can be resolved as the winner (logically wrong, though the data flow works).

**Why it happens:**
The current codebase uses plain strings for thread status with no validation layer. The developer follows the same pattern for candidate status: just a text column with no constraints. SQLite does not enforce enum values, so any string is accepted.

**How to avoid:**
1. Define valid candidate statuses as a union type: `"researching" | "ordered" | "arrived"` in `schemas.ts`
2. Add Zod validation for the status field with `.refine()` or `z.enum()` to reject invalid values at the API level
3. Define valid transitions: `researching -> ordered -> arrived` (and optionally `* -> dropped`)
4. In the service layer, validate that the requested status transition is valid before applying it (e.g., cannot go from "arrived" to "researching")
5. When resolving a thread, do NOT require a specific candidate status -- the user may resolve with a "researching" candidate if they decide to buy it outright. But DO update all non-winner candidates to a terminal state like "dropped" in the same transaction.
6. Add a check in `resolveThread`: if the thread is already resolved, reject the operation (this check already exists in the current code -- good)

**Warning signs:**
- Candidate status is a plain `text()` column with no Zod enum validation
- No transition validation in the update candidate service
- `resolveThread` does not update non-winner candidate statuses
- UI allows arbitrary status changes via a dropdown with no constraints

**Phase to address:**
Phase 3 (Candidate status tracking) -- must be designed with awareness of the existing thread resolution flow in `thread.service.ts`. The status field and transition logic should be added together, not incrementally.

---

### Pitfall 5: Weight Distribution Chart Diverges from Displayed Totals

**What goes wrong:**
The weight distribution chart (e.g., a donut chart showing weight by category or by classification) computes its data from one source, while the totals bar and setup detail page compute from another. The chart might use client-side summation of displayed (rounded) values while the totals use SQL `SUM()`. Or the chart uses the `useTotals()` hook data while the setup page computes totals inline (as `$setupId.tsx` currently does on lines 53-61). These different computation paths produce different numbers for the same data, and when a chart slice says "Shelter: 2,450g" but the category header says "Shelter: 2,451g," users lose trust.

**Why it happens:**
The codebase already has two computation paths for totals: `totals.service.ts` computes via SQL aggregates, and the setup detail page computes via JavaScript reduce on the client. These happen to agree now because there is no unit conversion, but adding unit display and classification filtering creates more opportunities for divergence.

**How to avoid:**
1. Establish a single source of truth for all weight computations: the SQL aggregate in the service layer.
2. For chart data, create a dedicated endpoint or extend `GET /api/totals` to return breakdowns by category AND by classification (for setups). Do not recompute in the chart component.
3. For setup-specific charts, extend `getSetupWithItems` to return pre-computed breakdowns, or compute them from the setup's item list using a shared utility function that is used by both the totals display and the chart.
4. Unit conversion happens once, at the display layer, using the same `formatWeight` function everywhere.
5. Write a test that compares the chart data source against the totals data source and asserts they agree.

**Warning signs:**
- Chart component does its own `reduce()` on item data instead of using the same data as the totals display
- Two different API endpoints return weight totals for the same scope and the values differ by small amounts
- Chart labels show different precision than text displays (chart: "2.4 kg", header: "2,451 g")
- No shared utility function for weight summation

**Phase to address:**
Phase 3 (Weight distribution visualization) -- but the single-source-of-truth pattern should be established in Phase 1 when refactoring formatters for unit selection.

---

### Pitfall 6: Schema Migration Breaks Test Helper

**What goes wrong:**
GearBox's test infrastructure uses a manual `createTestDb()` function in `tests/helpers/db.ts` that creates tables with raw SQL `CREATE TABLE` statements instead of using Drizzle's migration system. When adding new columns (e.g., `classification` to `setup_items`, `status` to `thread_candidates`, `weight_unit` to `settings`), the developer updates `src/db/schema.ts` and runs `bun run db:generate` + `bun run db:push`, but forgets to update the test helper's CREATE TABLE statements. All tests pass in the test database (which has the old schema) while the real database has the new schema -- or worse, tests fail with cryptic column-not-found errors and the developer wastes time debugging the wrong thing.

**Why it happens:**
The test helper duplicates the schema definition in raw SQL rather than deriving it from the Drizzle schema. This is a known pattern in the codebase (documented in CLAUDE.md: "When adding schema columns, update both `src/db/schema.ts` and the test helper's CREATE TABLE statements"). But under the pressure of adding multiple schema changes across several features, it is easy to miss one table or one column.

**How to avoid:**
1. **Every schema change PR must include the corresponding test helper update.** Add this as a checklist item in the development workflow.
2. Consider writing a simple validation test that compares the columns in `createTestDb()` tables against the Drizzle schema definition, failing if they diverge. This catches the problem automatically.
3. For v1.2, since multiple schema changes are landing (classification on setup_items, status on candidates, possibly weight_unit in settings), batch the test helper update and verify all changes in one pass.
4. Long-term: investigate using Drizzle's `migrate()` with in-memory SQLite to eliminate the duplication entirely.

**Warning signs:**
- Schema column added to `schema.ts` but not to `tests/helpers/db.ts`
- Tests pass locally but queries fail at runtime
- New service function works in the app but throws in tests
- Test database has fewer columns than production database

**Phase to address:**
Every phase that touches the schema. Must be addressed in Phase 1 (unit settings), Phase 2 (classification on setup_items), and Phase 3 (candidate status). Each phase should verify test helper parity as a completion criterion.

---

### Pitfall 7: Weight Unit Preference Stored Wrong, Applied Wrong

**What goes wrong:**
The developer stores the user's preferred weight unit as a setting (using the existing `settings` table with key-value pairs). But then applies it inconsistently: the collection page shows grams, the setup page shows ounces, the chart shows kilograms. Or the setting is read once on page load and cached in Zustand, so changing the preference requires a page refresh. Or the setting is read on every render, causing a flash of "g" before the "oz" preference loads.

**Why it happens:**
The `settings` table is a key-value store with no type safety. The preference is a string like `"oz"` that must be parsed and applied in many places: `formatWeight` in formatters, chart labels, totals bar, setup detail, item cards, category headers. Missing any one of these locations creates an inconsistency.

**How to avoid:**
1. Store the preference in the `settings` table as `{ key: "weightUnit", value: "g" | "oz" | "lb" | "kg" }`.
2. Create a `useWeightUnit()` hook that wraps `useSettings()` and returns the parsed unit with a fallback to `"g"`.
3. Modify `formatWeight` to accept a unit parameter: `formatWeight(grams, unit)`. This is a single function used everywhere, so changing it propagates automatically.
4. Do NOT store converted values anywhere -- always store grams, convert at display time.
5. Use React Query for the settings fetch so the preference is cached and shared across components. When the user changes their preference, invalidate `["settings"]` and all displays update simultaneously via React Query's reactivity.
6. Handle the loading state: show raw grams (or a loading skeleton) until the preference is loaded. Do not flash a different unit.

**Warning signs:**
- `formatWeight` does not accept a unit parameter -- it is hardcoded to `"g"`
- Weight unit preference is stored in Zustand instead of React Query (settings endpoint)
- Some components use `formatWeight` and some inline their own formatting
- Changing the unit preference does not update all visible weights without a page refresh

**Phase to address:**
Phase 1 (Weight unit selection) -- this is foundational infrastructure. The `formatWeight` refactor and `useWeightUnit` hook must exist before building any other feature that displays weight.

---

## Technical Debt Patterns

Shortcuts that seem reasonable but create long-term problems.

| Shortcut | Immediate Benefit | Long-term Cost | When Acceptable |
|----------|-------------------|----------------|-----------------|
| Adding classification to `items` instead of `setup_items` | Simpler schema, no join table changes | Cannot have different classifications per setup; future migration required | Never -- the per-setup model is the correct one |
| Client-side unit conversion on both read and write paths | Simple bidirectional conversion | Rounding drift over edit cycles, inconsistent totals | Never -- convert once on write, display-only on read |
| Separate chart data computation from totals computation | Faster chart development, no API changes | Numbers disagree between chart and text displays | Only if a shared utility function ensures identical computation |
| Hardcoding chart library colors per category | Quick to implement | Colors collide when user adds categories; no dark mode support | MVP only if using a predictable color generation function is planned |
| Adding candidate status without transition validation | Faster to implement | Invalid states accumulate, resolve logic has edge cases | Only if validation is added before the feature ships to production |
| Debouncing search instead of client-side filter | Familiar pattern from server-filtered apps | Unnecessary latency, complex cache management | Never for this app's scale (sub-500 items) |

## Integration Gotchas

Since v1.2 is adding features to an existing system rather than integrating external services, these are internal integration points where new features interact with existing ones.

| Integration Point | Common Mistake | Correct Approach |
|-------------------|----------------|------------------|
| Search/filter + category grouping | Filtering items breaks the existing category-grouped layout because the group headers disappear when no items match | Filter within groups: show category headers only for groups with matching items. Empty groups should hide, not show "no items." |
| Weight classification + existing setup totals | Adding classification changes how totals are computed (base weight vs total weight), but existing setup list cards show `totalWeight` which was previously "everything" | Keep `totalWeight` as the sum of all items. Add `baseWeight` as a new computed field (sum of items where classification = 'base'). Show both in the setup detail view. |
| Candidate status + thread resolution | Adding status to candidates but not updating `resolveThread` to handle it | The `resolveThread` transaction must set winner status to a terminal state and non-winners to "dropped." New candidates added to an already-resolved thread should be rejected. |
| Unit selection + React Query cache | Changing the weight unit preference does not invalidate the items cache because items are stored in grams regardless | The unit preference is a display concern, not a data concern. Do NOT invalidate items/totals on unit change. Just re-render with the new unit. Ensure `formatWeight` is called reactively, not cached. |
| Weight chart + empty/null weights | Chart component crashes or shows misleading data when items have `null` weight | Filter out items with null weight from chart data. Show a note like "3 items excluded (no weight recorded)." Never treat null as 0 in a chart -- that makes the chart lie. |

## Performance Traps

Patterns that work at small scale but fail as usage grows.

| Trap | Symptoms | Prevention | When It Breaks |
|------|----------|------------|----------------|
| Re-rendering entire collection on search keystroke | UI jank on every character typed in search box | Use `useMemo` to memoize the filtered list; ensure `ItemCard` is memoized with `React.memo` | 100+ items with images |
| Chart re-renders on every parent state change | Chart animation restarts on unrelated state updates (e.g., opening a panel) | Memoize chart data computation with `useMemo`; wrap chart component in `React.memo`; use `isAnimationActive={false}` after initial render | Any chart library with entrance animations |
| Recharts SVG rendering with many category slices | Donut chart becomes sluggish with 20+ categories, each with a tooltip and label | Limit chart to top N categories by weight, group the rest into "Other." Recharts is SVG-based, so keep segments under ~15. | 20+ categories (unlikely for single user, but possible) |
| Fetching settings on every component that displays weight | Waterfall of settings requests, or flash of unconverted weights | Use React Query with `staleTime: Infinity` for settings (they change rarely). Prefetch settings at app root. | First load of any page with weights |
| Computing classification breakdown per-render | Expensive reduce operations on every render cycle | Compute once in `useMemo` keyed on the items array and classification data | Setups with 50+ items (common for full bikepacking lists) |

## Security Mistakes

Domain-specific security issues beyond general web security.

| Mistake | Risk | Prevention |
|---------|------|------------|
| Candidate status field accepts arbitrary strings | SQLite text column accepts anything; UI may display unexpected values or XSS payloads in status badges | Validate status against enum in Zod schema. Reject unknown values at API level. Use `z.enum(["researching", "ordered", "arrived"])`. |
| Search query used in raw SQL LIKE | SQL injection if search string is interpolated into query (unlikely with Drizzle ORM but possible in raw SQL aggregates) | Use Drizzle's `like()` or `ilike()` operators which parameterize automatically. Never use template literals in `sql\`\`` with unsanitized user input. |
| Unit preference allows arbitrary values | Settings table stores any string; a crafted value could break formatWeight or cause display issues | Validate unit against `z.enum(["g", "oz", "lb", "kg"])` both on read and write. Use a typed constant for the allowed values. |

## UX Pitfalls

Common user experience mistakes in this domain.

| Pitfall | User Impact | Better Approach |
|---------|-------------|-----------------|
| Search clears when switching tabs (gear/planning/setups) | User searches for "tent," switches to planning to check threads, switches back and search is gone | Persist search query as a URL search parameter (`?tab=gear&q=tent`). TanStack Router already handles tab via search params. |
| Unit selection buried in settings page | User cannot quickly toggle between g and oz when comparing products listed in different units | Add a unit toggle/selector directly in the weight display area (e.g., in the TotalsBar or a small dropdown next to weight values). Keep global preference in settings, but allow quick access. |
| Classification picker adds friction to setup composition | User must classify every item when adding it to a setup, turning a quick "add to loadout" into a tedious process | Default all items to "base" classification. Allow bulk reclassification. Show classification as an optional second step after composing the setup. |
| Chart with no actionable insight | A pie chart showing "Shelter: 40%, Sleep: 25%, Cooking: 20%" is pretty but does not help the user make decisions | Pair the chart with a list sorted by weight. Highlight the heaviest category. If possible, show how the breakdown compares to "typical" or to other setups. At minimum, make chart segments clickable to filter to that category. |
| Status badges with no timestamps | User sees "ordered" but cannot remember when they ordered, or whether it has been suspiciously long | Store status change timestamps. Show relative time ("ordered 3 days ago"). Highlight statuses that have been stale too long ("ordered 30+ days ago -- still waiting?"). |
| Filter resets feel destructive | User applies multiple filters (category + search), then accidentally clears one and loses the other | Show active filters as dismissible chips/pills above the list. Each filter is independently clearable. A "clear all" button resets everything. |

## "Looks Done But Isn't" Checklist

Things that appear complete but are missing critical pieces.

- [ ] **Search/filter:** Often missing keyboard shortcut (Cmd/Ctrl+K to focus search) -- verify search is easily accessible without mouse
- [ ] **Search/filter:** Often missing empty state for "no results" -- verify a helpful message appears when search matches nothing, distinct from "collection is empty"
- [ ] **Weight classification:** Often missing the per-setup model -- verify the same item can have different classifications in different setups
- [ ] **Weight classification:** Often missing "unclassified" handling -- verify items with no classification default to "base" in all computations
- [ ] **Weight chart:** Often missing null-weight items -- verify items without weight data are excluded from chart with a visible note, not silently treated as 0g
- [ ] **Weight chart:** Often missing responsiveness -- verify chart renders correctly on mobile widths (Recharts needs `ResponsiveContainer` wrapper)
- [ ] **Candidate status:** Often missing transition validation -- verify a candidate cannot go from "arrived" back to "researching"
- [ ] **Candidate status:** Often missing integration with thread resolution -- verify resolving a thread updates all candidate statuses appropriately
- [ ] **Unit selection:** Often missing consistent application -- verify every weight display in the app (cards, headers, totals, charts, setup detail, item picker) uses the selected unit
- [ ] **Unit selection:** Often missing the edit form -- verify the item/candidate edit form shows weight in the selected unit and converts correctly on save
- [ ] **Unit selection:** Often missing chart axis labels -- verify the chart shows the correct unit in labels and tooltips

## Recovery Strategies

When pitfalls occur despite prevention, how to recover.

| Pitfall | Recovery Cost | Recovery Steps |
|---------|---------------|----------------|
| Classification on items instead of setup_items | HIGH | Add classification column to setup_items. Write migration to copy item classification to all setup_item rows referencing it. Remove classification from items. Review all service queries. |
| Rounding drift from bidirectional conversion | MEDIUM | Audit all items for drift (compare stored grams to expected values). Fix formatWeight to convert only at display. One-time data cleanup for items with suspicious fractional grams. |
| Chart data disagrees with totals | LOW | Refactor chart to use the same data source as totals. Create shared utility. No data migration needed. |
| Test helper out of sync with schema | LOW | Update CREATE TABLE statements in test helper. Run all tests. Fix any that relied on the old schema. |
| Server-side search causing cache issues | MEDIUM | Revert to client-side filtering. Remove query params from useItems. May need to clear stale React Query cache entries with different keys. |
| Candidate status without transitions | MEDIUM | Add transition validation to update endpoint. Audit existing candidates for invalid states. Write cleanup migration if needed. |
| Unit preference inconsistently applied | LOW | Audit all weight display points. Ensure all use formatWeight with unit parameter. No data changes needed. |

## Pitfall-to-Phase Mapping

How roadmap phases should address these pitfalls.

| Pitfall | Prevention Phase | Verification |
|---------|------------------|--------------|
| Rounding accumulation | Phase 1: Weight unit selection | `formatWeight` converts grams to display unit. Edit forms load grams from API, not from displayed value. Write test: edit an item 10 times without changes, weight stays identical. |
| Classification at wrong level | Phase 2: Weight classification | `classification` column exists on `setup_items`, not `items`. Test: same item in two setups has different classifications. |
| Server-side search for client data | Phase 1: Search/filter | No new API parameters on `GET /api/items`. Filter logic lives in `CollectionView` component. Test: search works instantly without network requests. |
| Status without transition validation | Phase 3: Candidate status | Zod enum validates status values. Service rejects invalid transitions. Test: updating "arrived" to "researching" returns 400 error. |
| Chart/totals divergence | Phase 3: Weight visualization | Chart data and totals bar use same computation path. Test: sum of chart segment values equals displayed total. |
| Test helper desync | Every schema-changing phase | Each phase's PR includes updated test helper. CI test suite catches column mismatches. |
| Unit preference inconsistency | Phase 1: Weight unit selection | All weight displays use `formatWeight(grams, unit)`. Test: change unit preference, verify all visible weights update without refresh. |

## Sources

- [Weight conversion precision and rounding best practices](https://explore.st-aug.edu/exp/from-ounces-to-pounds-the-precision-behind-weight-conversions-heres-how-many-grams-equal-a-practical-pound) -- authoritative source on conversion factor precision
- [Base weight classification definitions and community debates](https://thetrek.co/continental-divide-trail/how-to-easily-lower-your-base-weight-calculate-it-differently/) -- real-world examples of classification ambiguity
- [LighterPack user classification errors](https://www.99boulders.com/lighterpack-tutorial) -- LighterPack's approach to base/worn/consumable
- [Avoiding common mistakes with TanStack Query](https://www.buncolak.com/posts/avoiding-common-mistakes-with-tanstack-query-part-1/) -- anti-patterns with React Query caching
- [TanStack Query discussions on filtering with cache](https://github.com/TanStack/query/discussions/1113) -- community patterns for client-side vs server-side filtering
- [Recharts performance and limitations](https://blog.logrocket.com/best-react-chart-libraries-2025/) -- SVG rendering pitfalls, ResponsiveContainer requirement
- [Drizzle ORM SQLite migration pitfalls](https://github.com/drizzle-team/drizzle-orm/issues/1313) -- data loss bug with push + add column
- [State machine anti-patterns](https://rclayton.silvrback.com/use-state-machines) -- importance of explicit transition validation
- [Ultralight gear tracker leaving LighterPack](https://trailsmag.net/blogs/hiker-box/ultralight-the-gear-tracking-app-i-m-leaving-lighterpack-for) -- community frustrations with existing tools
- Direct codebase analysis of GearBox v1.1 (schema.ts, services, hooks, routes) -- existing patterns and integration points

---
*Pitfalls research for: GearBox v1.2 -- Collection Power-Ups (search/filter, weight classification, charts, candidate status, unit selection)*
*Researched: 2026-03-16*