菜单
Structured approach to code generation, implementing features, and writing code. Use when asked to generate code, implement a feature, write code, or tackle a coding task. Analyzes the task, generates multiple approaches with trade-offs, selects the optimal solution, and implements it.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Post-implementation verification protocol that catches incomplete work, hidden shortcuts, and gaps between 'tests pass' and 'production works.' Systematically traces data chains, detects placeholders, audits test honesty, and verifies environment parity. Use when asked to: verify implementation, check completeness, implementation review, is this done, built properly, no shortcuts, verify work, completion check, integrity check, self-review, pre-PR check, ship check.
Lightweight project management system designed for human-agent collaboration, optimized for context preservation across sessions. Use when asked to: project management, project setup, project tracking, synthesis project, manage project, set up project, project structure, session protocol.
Validate, convert, and author content for Google's Open Knowledge Format (OKF v0.1) — the markdown-plus-YAML-frontmatter knowledge-bundle spec announced 2026-06-12. Includes a conformance validator (the checker Google's own OKF repo ships none of), a converter that backfills OKF frontmatter onto an existing markdown corpus idempotently, and the proven repo-by-repo conversion procedure. Use when adopting OKF for an "LLM wiki" style knowledge base, auditing conformance, or converting a corpus of markdown notes/docs into a conformant, agent-readable bundle.
Discipline for catching the lazy-shortcut antipattern in AI-assistant output. Makes the costume vocabulary explicit so agents recognize when their drafts have slid into deferral, dismissal, or false consultation. Includes the constraint-first protocol, sub-agent dispatch and acceptance hygiene, and a pre-response self-check. Use when asked to: avoid shortcuts, audit for laziness, check for deferral, enforce best solution, no shortcuts, anti-shortcut, constraint-first, sub-agent hygiene, costume vocabulary.
Cross-provider model-tier convention for agentic work: three role labels (judgment, routine, bulk — formerly frontier, efficient, light) resolved to current model IDs per provider in tiers.yaml, so skills, project docs, and memory never hardcode model names. Use when asked about: model tiers, which model, model selection, judgment model, routine model, bulk model, frontier model, efficient model, switch models, model equivalents across providers, update model table.
Fetch AI-generated meeting notes and full transcripts (e.g., Google Meet + Gemini) from the user's Gmail/Drive into local markdown files. Tool-agnostic: works with any Gmail + Drive MCP (Anthropic hosted connectors, self-hosted workspace-mcp, or others). Replaces the manual email → Google Doc → export-markdown → Downloads → move workflow. Use when asked to: fetch meeting transcript, pull standup, grab meeting notes, sync meetings, download transcript, get Gemini notes, import meeting.
| name | synthesis-code-planning |
| description | Structured approach to code generation, implementing features, and writing code. Use when asked to generate code, implement a feature, write code, or tackle a coding task. Analyzes the task, generates multiple approaches with trade-offs, selects the optimal solution, and implements it. |
| license | CC0-1.0 |
| user-invocable | false |
| depends_on | [] |
| metadata | {"author":"Rajiv Pant","version":"1.0.0","source_repo":"github.com/synthesisengineering/synthesis-skills","source_type":"public"} |
A structured methodology for approaching code tasks that produces higher-quality implementations by evaluating multiple approaches before committing to one.
Before generating code, gather three inputs:
Carefully analyze the task description and existing code. Consider:
Produce at least two distinct approaches to address the task. For each approach, document:
Approach 1: [Brief description]
Approach 2: [Brief description]
Generate more approaches when the problem space is ambiguous or when the first two approaches have significant trade-offs against each other.
Select the optimal solution and justify the choice with specific reasoning:
Implement the chosen solution by modifying or creating code:
For trivial changes (typo fixes, single-line config changes, renaming a variable), skip Steps 2-3 and implement directly. The threshold: if the implementation is obvious and unambiguous, proceed without generating alternatives.
