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Defer sort seed checks until adjust-order startup

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夏斯雷
2026-05-22 22:44:56 +08:00
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# Code Reuse Thinking Guide
> **Purpose**: Stop and think before creating new code - does it already exist?
---
## The Problem
**Duplicated code is the #1 source of inconsistency bugs.**
When you copy-paste or rewrite existing logic:
- Bug fixes don't propagate
- Behavior diverges over time
- Codebase becomes harder to understand
---
## Before Writing New Code
### Step 1: Search First
```bash
# Search for similar function names
grep -r "functionName" .
# Search for similar logic
grep -r "keyword" .
```
### Step 2: Ask These Questions
| Question | If Yes... |
|----------|-----------|
| Does a similar function exist? | Use or extend it |
| Is this pattern used elsewhere? | Follow the existing pattern |
| Could this be a shared utility? | Create it in the right place |
| Am I copying code from another file? | **STOP** - extract to shared |
---
## Common Duplication Patterns
### Pattern 1: Copy-Paste Functions
**Bad**: Copying a validation function to another file
**Good**: Extract to shared utilities, import where needed
### Pattern 2: Similar Components
**Bad**: Creating a new component that's 80% similar to existing
**Good**: Extend existing component with props/variants
### Pattern 3: Repeated Constants
**Bad**: Defining the same constant in multiple files
**Good**: Single source of truth, import everywhere
---
## When to Abstract
**Abstract when**:
- Same code appears 3+ times
- Logic is complex enough to have bugs
- Multiple people might need this
**Don't abstract when**:
- Only used once
- Trivial one-liner
- Abstraction would be more complex than duplication
---
## After Batch Modifications
When you've made similar changes to multiple files:
1. **Review**: Did you catch all instances?
2. **Search**: Run grep to find any missed
3. **Consider**: Should this be abstracted?
---
## Gotcha: Asymmetric Mechanisms Producing Same Output
**Problem**: When two different mechanisms must produce the same file set (e.g., recursive directory copy for init vs. manual `files.set()` for update), structural changes (renaming, moving, adding subdirectories) only propagate through the automatic mechanism. The manual one silently drifts.
**Symptom**: Init works perfectly, but update creates files at wrong paths or misses files entirely.
**Prevention checklist**:
- [ ] When migrating directory structures, search for ALL code paths that reference the old structure
- [ ] If one path is auto-derived (glob/copy) and another is manually listed, the manual one needs updating
- [ ] Add a regression test that compares outputs from both mechanisms
---
## Checklist Before Commit
- [ ] Searched for existing similar code
- [ ] No copy-pasted logic that should be shared
- [ ] Constants defined in one place
- [ ] Similar patterns follow same structure

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# Cross-Layer Thinking Guide
> **Purpose**: Think through data flow across layers before implementing.
---
## The Problem
**Most bugs happen at layer boundaries**, not within layers.
Common cross-layer bugs:
- API returns format A, frontend expects format B
- Database stores X, service transforms to Y, but loses data
- Multiple layers implement the same logic differently
---
## Before Implementing Cross-Layer Features
### Step 1: Map the Data Flow
Draw out how data moves:
```
Source → Transform → Store → Retrieve → Transform → Display
```
For each arrow, ask:
- What format is the data in?
- What could go wrong?
- Who is responsible for validation?
### Step 2: Identify Boundaries
| Boundary | Common Issues |
|----------|---------------|
| API ↔ Service | Type mismatches, missing fields |
| Service ↔ Database | Format conversions, null handling |
| Backend ↔ Frontend | Serialization, date formats |
| Component ↔ Component | Props shape changes |
### Step 3: Define Contracts
For each boundary:
- What is the exact input format?
- What is the exact output format?
- What errors can occur?
---
## Common Cross-Layer Mistakes
### Mistake 1: Implicit Format Assumptions
**Bad**: Assuming date format without checking
**Good**: Explicit format conversion at boundaries
### Mistake 2: Scattered Validation
**Bad**: Validating the same thing in multiple layers
**Good**: Validate once at the entry point
### Mistake 3: Leaky Abstractions
**Bad**: Component knows about database schema
**Good**: Each layer only knows its neighbors
---
## Checklist for Cross-Layer Features
Before implementation:
- [ ] Mapped the complete data flow
- [ ] Identified all layer boundaries
- [ ] Defined format at each boundary
- [ ] Decided where validation happens
After implementation:
- [ ] Tested with edge cases (null, empty, invalid)
- [ ] Verified error handling at each boundary
- [ ] Checked data survives round-trip
---
## Cross-Platform Template Consistency
In Trellis, command templates (e.g., `record-session.md`) exist in **multiple platforms** with identical or near-identical content. This is a cross-layer boundary.
### Checklist: After Modifying Any Command Template
- [ ] Find all platforms with the same command: `find src/templates/*/commands/trellis/ -name "<command>.*"`
- [ ] Update all platform copies (Markdown `.md` and TOML `.toml`)
- [ ] For Gemini TOML: adapt line continuations (`\\` vs `\`) and triple-quoted strings
- [ ] Run `/trellis:check-cross-layer` to verify nothing was missed
**Real-world example**: Updated `record-session.md` in Claude to use `--mode record`, but forgot iFlow, Kilo, OpenCode, and Gemini — caught by cross-layer check.
---
## Generated Runtime Template Upgrade Consistency
Some generated files are both documentation and runtime input. In Trellis,
`.trellis/workflow.md` is parsed by `get_context.py`, `workflow_phase.py`,
SessionStart filters, and per-turn hooks. Template changes must be validated
against both fresh init and upgrade paths.
### Checklist: After Modifying A Runtime-Parsed Template
- [ ] Identify every runtime parser that reads the template, not just the file
writer that installs it
- [ ] Check whether relevant syntax lives outside obvious managed regions
such as tag blocks
- [ ] Verify fresh `init` output and a versioned `update` scenario that writes
the older `.trellis/.version`
- [ ] Add an upgrade regression using an older pristine template fixture, then
assert the installed file reaches the current packaged shape
- [ ] Update the backend spec that owns the runtime contract
**Real-world example**: Codex inline mode changed workflow platform markers from
`[Codex]` / `[Kilo, Antigravity, Windsurf]` to `[codex-sub-agent]` /
`[codex-inline, Kilo, Antigravity, Windsurf]`. Fresh init was correct, but
`trellis update` only merged `[workflow-state:*]` blocks and preserved stale
markers outside those blocks. Result: upgraded projects got new hook scripts
but old workflow routing, so `get_context.py --mode phase --platform codex`
could return empty Phase 2.1 detail.
---
## Mode-Detection Probe Checklist
When a CLI auto-detects a mode by probing a remote resource (e.g., checking if `index.json` exists to decide marketplace vs direct download):
### Before implementing:
- [ ] Probe runs in **ALL** code paths that use the result (interactive, `-y`, `--flag` combos)
- [ ] 404 vs transient error are distinguished — don't treat both as "not found"
- [ ] Transient errors **abort or retry**, never silently switch modes
- [ ] Shared state (caches, prefetched data) is **reset** when context changes (e.g., user switches source)
- [ ] **Shortcut paths** (e.g., `--template` skipping picker) must have the same error-handling quality as the probed path — check that downstream functions don't call catch-all wrappers
### After implementing:
- [ ] Trace every path from probe result to the mode-decision branch — no fallthrough
- [ ] External format contracts (giget URI, raw URLs) are tested or at least documented as comments
- [ ] Metadata reads consume a complete response or use a streaming parser — never parse a fixed-size prefix as full JSON
- [ ] When reconstructing a composite identifier from parsed parts, verify **all** fields are included and in the **correct position** (e.g., `provider:repo/path#ref` not `provider:repo#ref/path`)
- [ ] Verify that **action functions** called after a shortcut don't internally use the old catch-all fetch — they must use the probe-quality variant when error distinction matters
**Real-world example**: Custom registry flow had 8 bugs across 3 review rounds: (1) probe only ran in interactive mode, (2) transient errors fell through to wrong mode, (3) giget URI had `#ref` in wrong position, (4) prefetched templates leaked across source switches, (5) `--template` shortcut bypassed probe but `downloadTemplateById` internally used catch-all `fetchTemplateIndex`, turning timeouts into "Template not found".
**Real-world example**: Agent-session update hints fetched npm `latest` metadata with `response.read(4096)` and then parsed it as complete JSON. The `@mindfoldhq/trellis` package metadata exceeded 4 KB, so the JSON was truncated, parse failed silently, and the first session injection showed no update hint. Fix: read the complete response before parsing, and add a regression where `version` is followed by an 8 KB metadata tail.
---
## When to Create Flow Documentation
Create detailed flow docs when:
- Feature spans 3+ layers
- Multiple teams are involved
- Data format is complex
- Feature has caused bugs before

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# Thinking Guides
> **Purpose**: Expand your thinking to catch things you might not have considered.
---
## Why Thinking Guides?
**Most bugs and tech debt come from "didn't think of that"**, not from lack of skill:
- Didn't think about what happens at layer boundaries → cross-layer bugs
- Didn't think about code patterns repeating → duplicated code everywhere
- Didn't think about edge cases → runtime errors
- Didn't think about future maintainers → unreadable code
These guides help you **ask the right questions before coding**.
---
## Available Guides
| Guide | Purpose | When to Use |
|-------|---------|-------------|
| [Code Reuse Thinking Guide](./code-reuse-thinking-guide.md) | Identify patterns and reduce duplication | When you notice repeated patterns |
| [Cross-Layer Thinking Guide](./cross-layer-thinking-guide.md) | Think through data flow across layers | Features spanning multiple layers |
---
## Quick Reference: Thinking Triggers
### When to Think About Cross-Layer Issues
- [ ] Feature touches 3+ layers (API, Service, Component, Database)
- [ ] Data format changes between layers
- [ ] Multiple consumers need the same data
- [ ] You're not sure where to put some logic
→ Read [Cross-Layer Thinking Guide](./cross-layer-thinking-guide.md)
### When to Think About Code Reuse
- [ ] You're writing similar code to something that exists
- [ ] You see the same pattern repeated 3+ times
- [ ] You're adding a new field to multiple places
- [ ] **You're modifying any constant or config**
- [ ] **You're creating a new utility/helper function** ← Search first!
→ Read [Code Reuse Thinking Guide](./code-reuse-thinking-guide.md)
---
## Pre-Modification Rule (CRITICAL)
> **Before changing ANY value, ALWAYS search first!**
```bash
# Search for the value you're about to change
grep -r "value_to_change" .
```
This single habit prevents most "forgot to update X" bugs.
---
## How to Use This Directory
1. **Before coding**: Skim the relevant thinking guide
2. **During coding**: If something feels repetitive or complex, check the guides
3. **After bugs**: Add new insights to the relevant guide (learn from mistakes)
---
## Contributing
Found a new "didn't think of that" moment? Add it to the relevant guide.
---
**Core Principle**: 30 minutes of thinking saves 3 hours of debugging.