Skip to content
FunCoding

Search

Search docs, Skills and MCP

trellis-update-spec

Captures executable contracts and coding conventions into .trellis/spec/ documents. Use when learning something valuable from debugging, implementing, or discussion that should be preserved for future sessions.

代码质量与审查1.8k.cursor/skills/trellis-update-spec/SKILL.md

Install

Send this to Claude Code, Codex or Cursor. The agent checks the Skill for safety first and installs it only after you confirm.

读取 https://funcoding.ai/skills/fy-agent/fyagent/cursor-skills-trellis-update-spec/install.md ,按里面的步骤帮我安装这个 Skill。

SKILL.md

Update Code-Spec - Capture Executable Contracts

When you learn something valuable (from debugging, implementing, or discussion), use this to update the relevant code-spec documents.

Timing: After completing a task, fixing a bug, or discovering a new pattern


Code-Spec First Rule (CRITICAL)

In this project, "spec" for implementation work means code-spec:

  • Executable contracts (not principle-only text)
  • Concrete signatures, payload fields, env keys, and boundary behavior
  • Testable validation/error behavior

If the change touches infra or cross-layer contracts, code-spec depth is mandatory.

Mandatory Triggers

Apply code-spec depth when the change includes any of:

  • New/changed command or API signature
  • Cross-layer request/response contract change
  • Database schema/migration change
  • Infra integration (storage, queue, cache, secrets, env wiring)

Mandatory Output (7 Sections)

For triggered tasks, include all sections below:

  1. Scope / Trigger
  2. Signatures (command/API/DB)
  3. Contracts (request/response/env)
  4. Validation & Error Matrix
  5. Good/Base/Bad Cases
  6. Tests Required (with assertion points)
  7. Wrong vs Correct (at least one pair)

When to Update Code-Specs

TriggerExampleTarget Spec
Implemented a featureAdded a new integration or moduleRelevant spec file
Made a design decisionChose extensibility pattern over simplicityRelevant spec + "Design Decisions" section
Fixed a bugFound a subtle issue with error handlingRelevant spec (e.g., error-handling docs)
Discovered a patternFound a better way to structure codeRelevant spec file
Hit a gotchaLearned that X must be done before YRelevant spec + "Common Mistakes" section
Established a conventionTeam agreed on naming patternQuality guidelines
New thinking trigger"Don't forget to check X before doing Y"guides/*.md (as a checklist item)

Key Insight: Code-spec updates are NOT just for problems. Every feature implementation contains design decisions and contracts that future AI/developers need to execute safely.


Spec Structure Overview

.trellis/spec/
├── <layer>/           # Per-layer coding standards (e.g., backend/, frontend/, api/)
│   ├── index.md       # Overview and links
│   └── *.md           # Topic-specific guidelines
└── guides/            # Thinking checklists (NOT coding specs!)
    ├── index.md       # Guide index
    └── *.md           # Topic-specific guides

CRITICAL: Code-Spec vs Guide - Know the Difference

TypeLocationPurposeContent Style
Code-Spec<layer>/*.mdTell AI "how to implement safely"Signatures, contracts, matrices, cases, test points
Guideguides/*.mdHelp AI "what to think about"Checklists, questions, pointers to specs

Decision Rule: Ask yourself:

  • "This is how to write the code" → Put in a spec layer directory
  • "This is what to consider before writing" → Put in guides/

Example:

LearningWrong LocationCorrect Location
"Use API X not API Y for this task"❌ guides/ (too specific for a thinking guide)✅ Relevant spec file (concrete convention)
"Remember to check X when doing Y"❌ Spec file (too abstract for a spec)✅ guides/ (thinking checklist)

Guides should be short checklists that point to specs, not duplicate the detailed rules.


Update Process

Step 1: Identify What You Learned

Answer these questions:

  1. What did you learn? (Be specific)
  2. Why is it important? (What problem does it prevent?)
  3. Where does it belong? (Which spec file?)

Step 2: Classify the Update Type

TypeDescriptionAction
Design DecisionWhy we chose approach X over YAdd to "Design Decisions" section
Project ConventionHow we do X in this projectAdd to relevant section with examples
New PatternA reusable approach discoveredAdd to "Patterns" section
Forbidden PatternSomething that causes problemsAdd to "Anti-patterns" or "Don't" section
Common MistakeEasy-to-make errorAdd to "Common Mistakes" section
ConventionAgreed-upon standardAdd to relevant section
GotchaNon-obvious behaviorAdd warning callout

Step 3: Read the Target Code-Spec

Before editing, read the current code-spec to:

  • Understand existing structure
  • Avoid duplicating content
  • Find the right section for your update
cat .trellis/spec/<category>/<file>.md

Step 4: Make the Update

Follow these principles:

  1. Be Specific: Include concrete examples, not just abstract rules
  2. Explain Why: State the problem this prevents
  3. Show Contracts: Add signatures, payload fields, and error behavior
  4. Show Code: Add code snippets for key patterns
  5. Keep it Short: One concept per section

Step 5: Update the Index (if needed)

If you added a new section or the code-spec status changed, update the category's index.md.


Update Templates

Mandatory Template for Infra/Cross-Layer Work

## Scenario: <name>

### 1. Scope / Trigger
- Trigger: <why this requires code-spec depth>

### 2. Signatures
- Backend command/API/DB signature(s)

### 3. Contracts
- Request fields (name, type, constraints)
- Response fields (name, type, constraints)
- Environment keys (required/optional)

### 4. Validation & Error Matrix
- <condition> -> <error>

### 5. Good/Base/Bad Cases
- Good: ...
- Base: ...
- Bad: ...

### 6. Tests Required
- Unit/Integration/E2E with assertion points

### 7. Wrong vs Correct
#### Wrong
...
#### Correct
...

Adding a Design Decision

### Design Decision: [Decision Name]

**Context**: What problem were we solving?

**Options Considered**:
1. Option A - brief description
2. Option B - brief description

**Decision**: We chose Option X because...

**Example**:
\`\`\`typescript
// How it's implemented
code example
\`\`\`

**Extensibility**: How to extend this in the future...

Adding a Project Convention

### Convention: [Convention Name]

**What**: Brief description of the convention.

**Why**: Why we do it this way in this project.

**Example**:
\`\`\`typescript
// How to follow this convention
code example
\`\`\`

**Related**: Links to related conventions or specs.

Adding a New Pattern

### Pattern Name

**Problem**: What problem does this solve?

**Solution**: Brief description of the approach.

**Example**:
\`\`\`
// Good
code example

// Bad
code example
\`\`\`

**Why**: Explanation of why this works better.

Adding a Forbidden Pattern

### Don't: Pattern Name

**Problem**:
\`\`\`
// Don't do this
bad code example
\`\`\`

**Why it's bad**: Explanation of the issue.

**Instead**:
\`\`\`
// Do this instead
good code example
\`\`\`

Adding a Common Mistake

### Common Mistake: Description

**Symptom**: What goes wrong

**Cause**: Why this happens

**Fix**: How to correct it

**Prevention**: How to avoid it in the future

Adding a Gotcha

> **Warning**: Brief description of the non-obvious behavior.
>
> Details about when this happens and how to handle it.

Interactive Mode

If you're unsure what to update, answer these prompts:

  1. What did you just finish?

    • Fixed a bug
    • Implemented a feature
    • Refactored code
    • Had a discussion about approach
  2. What did you learn or decide?

    • Design decision (why X over Y)
    • Project convention (how we do X)
    • Non-obvious behavior (gotcha)
    • Better approach (pattern)
  3. Would future AI/developers need to know this?

    • To understand how the code works → Yes, update spec
    • To maintain or extend the feature → Yes, update spec
    • To avoid repeating mistakes → Yes, update spec
    • Purely one-off implementation detail → Maybe skip
  4. Which area does it relate to?

    • Backend code
    • Frontend code
    • Cross-layer data flow
    • Code organization/reuse
    • Quality/testing

Quality Checklist

Before finishing your code-spec update:

  • Is the content specific and actionable?
  • Did you include a code example?
  • Did you explain WHY, not just WHAT?
  • Did you include executable signatures/contracts?
  • Did you include validation and error matrix?
  • Did you include Good/Base/Bad cases?
  • Did you include required tests with assertion points?
  • Is it in the right code-spec file?
  • Does it duplicate existing content?
  • Would a new team member understand it?

Relationship to Other Commands

Development Flow:
  Learn something → /trellis-update-spec → Knowledge captured
       ↑                                  ↓
  /trellis-break-loop ←──────────────────── Future sessions benefit
  (deep bug analysis)
  • /trellis-break-loop - Analyzes bugs deeply, often reveals spec updates needed
  • /trellis-update-spec - Actually makes the updates
  • /trellis-finish-work - Reminds you to check if specs need updates

Core Philosophy

Code-specs are living documents. Every debugging session, every "aha moment" is an opportunity to make the implementation contract clearer.

The goal is institutional memory:

  • What one person learns, everyone benefits from
  • What AI learns in one session, persists to future sessions
  • Mistakes become documented guardrails

Similar Skills

claude-api
anthropics/skills180k

claude-api

Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration. TRIGGER — read BEFORE opening the target file; don't skip because it "looks like a one-liner" — whenever: the prompt names Claude/Anthropic in any form (Claude, Anthropic, Fable, Opus, Sonnet, Haiku, `anthropic`, `@anthropic-ai`, `claude-*`, `us.anthropic.*`, `[1m]`); the user asks about an LLM (pricing/model choice/limits/caching) — never answer from memory; OR the task is LLM-shaped with provider unstated (agent/MCP/tool-definition/multi-agent/RAG/LLM-judge/computer-use; generate/summarize/extract/classify/rewrite/converse over NL; debugging refusals/cutoffs/streaming/tool-calls/tokens). SKIP only when another provider is being worked on (overrides all triggers): OpenAI/GPT/Gemini/Llama/Mistral/Cohere/Ollama named in the query; OR `grep -rE 'openai|langchain_openai|google.generativeai|genai|mistralai|cohere|ollama'` over the project hits (run this grep FIRST if no provider named — don't Read the file).

Code quality & review

ponytail-review
DietrichGebert/ponytail158k

ponytail-review

Quality review of a change: is the logic right, is it safe, does it hold under real load, is risky code tested, is it fast enough, and is every line needed. Reads the connected code, not only the diff. Each finding is explained in plain English. Use for "review this", "code review", "review the last commit", "review my PR", "is this over-engineered", /ponytail-review.

Code quality & review

code-review-and-quality
addyosmani/agent-skills103k

code-review-and-quality

Conducts multi-axis code review. Use before merging any change. Use when reviewing code written by yourself, another agent, or a human. Use when you need to assess code quality across multiple dimensions before it enters the main branch. Use when asked to review a diff or a pull request, even when the diff is pasted inline.

Code quality & review

documentation-and-adrs
addyosmani/agent-skills103k

documentation-and-adrs

Records decisions and documentation. Use when you need to document an architecture decision (ADR) or the reasoning behind a design choice, when changing public APIs, shipping features, or when you need to record context that future engineers and agents will need to understand the codebase.

Code quality & review

code-simplification
addyosmani/agent-skills103k

code-simplification

Simplifies code for clarity. Use when refactoring code for clarity without changing behavior. Use when code works but is harder to read, maintain, or extend than it should be. Use when reviewing code that has accumulated unnecessary complexity.

Code quality & review

understand
Egonex-AI/Understand-Anything86k

understand

Analyze a codebase to produce an interactive knowledge graph for understanding architecture, components, and relationships

Code quality & review