skills/go-project/SKILL.md
Guide for advancing a project implementation by executing tasks from an existing PLAN.md and TODO.md, and keeping the documentation in sync with actual progress. Use this skill whenever the user wants to continue working on a project, implement the next steps, make progress on planned tasks, or says things like 'let's continue', 'next step', 'implement this', 'do the next task', or references an existing PLAN.md or TODO.md. Also use when the user asks to build, code, or implement something that is already described in docs/PLAN.md or docs/TODO.md.
npx skillsauth add hrdtbs/agent-skills go-projectInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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When an AI agent resumes work on a project that has an existing docs/PLAN.md and docs/TODO.md, the agent must read these files first, understand the current state, execute the next task, and update the documentation to reflect progress. This skill ensures continuity between sessions and prevents the agent from re-deriving the plan or deviating from established decisions.
When the user asks you to continue, implement, or make progress on a project, follow this workflow:
docs/PLAN.md, docs/TODO.md, and any files in docs/references/ if they exist. Understand the design decisions already made and what tasks remain.[x]. Reveal the next task as the new "Next immediate step." If new tasks were discovered during implementation, add them. Remove the "Next immediate step" section and recreate it at the top with the new next task.docs/references/ instead of keeping them in context. Follow the same guidelines as the create-project skill: write in markdown, include the source at the top, summarize key findings, and note trade-offs or caveats.User: "Let's continue with the CSV to JSON CLI tool. Implement the core logic."
Agent action:
docs/PLAN.md — confirms: single Python script, stdlib only, csv.DictReader → json.dump.docs/TODO.md — next immediate step is "Implement csv_to_json() function."csv_to_json.py with the core logic matching the plan.docs/TODO.md:
csv_to_json() function" as [x].argparse."csv_to_json() function. It reads CSV via DictReader and outputs formatted JSON. The next step is to add the CLI interface. I've updated docs/TODO.md."testing
Evaluate Agent Skill design quality against official specifications and best practices. Use when reviewing, auditing, or improving SKILL.md files and skill packages. Provides multi-dimensional scoring and actionable improvement suggestions.
testing
Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
development
Evaluate and score user-written LLM prompts on a 100-point scale across 5 axes (Clarity, Structure, Information Content, Specificity, Context), providing specific improvement suggestions and a revised prompt. Make sure to use this skill whenever the user asks to evaluate, review, score, or improve a prompt, or when they say things like 'このプロンプトどう?', 'プロンプトを評価して', 'rate my prompt', 'review this prompt', or 'is this prompt good enough?'. This skill focuses on scoring existing prompts, not writing new ones from scratch.
testing
Apply prompt engineering best practices to write, refine, and optimize system prompts, user prompts, and agent instructions. Use this skill whenever the user wants to write a prompt, optimize an existing prompt for better results, fix a prompt that is hallucinating or underperforming, or structure prompts for Large Language Models (LLMs). Even if the user just says "help me write instructions for my agent", trigger this skill.