Agent skill · Design & Presentation

project-development

This skill should be used for project-level decisions about LLM-powered systems: whether an LLM is the right primitive for the task at hand, the shape of a multi-stage batch or agent pipeline, token and cost estimation, choosing between single-agent and multi-agent at the project level, structured output design for downstream parsing, and structuring agent-assisted iteration. Use this when the unit of work is a whole project or a multi-stage pipeline. Route individual tool design to tool-design and individual skill-loading or context-budget tactics to context-optimization.

guanyanggithub.com/guanyangGitHub ↗
claude-codeships scriptsMIT
Install
npx skills add guanyang/open-agent-hub --skill project-development --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 4
SKILL.md size: 19 KB
Bundled scripts: yes
Path: skills/project-development/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 940
Language: TypeScript

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Project Development Methodology This skill covers the principles for identifying tasks suited to LLM processing, designing effective project architectures, and iterating rapidly using agent-assisted development. The methodology applies whether building a batch processing pipeline, a multi-agent research system, or an interactive agent application. The unit of work for this skill is the whole project or a multi-stage pipeline. Individual tool design (descriptions, schemas, error messages) belongs to `tool-design`. Per-skill activation routing belongs to the corresponding skill plus the corpus index. This skill owns the project-level questions: should you build this with an LLM at all, what shape should the pipeline take, what does it cost, how should it be iterated. ## When to Activate Activate this skill when the unit of work is a whole project or pipeline: - Deciding whether an LLM is the right primitive for a task at all (task-model fit before any code). - Shaping a multi-stage batch or agent pipeline (acquire / prepare / process / parse / render). - Estimating tokens, dollar cost, and timelines for an LLM-heavy project. - Choosing between single-agent and multi-agent at the pr

What's inside
Steps it walks through
  1. When to Activate
  2. Core Concepts
  3. Task-Model Fit Recognition
  4. The Manual Prototype Step
  5. Pipeline Architecture
  6. File System as State Machine
  7. Structured Output Design
  8. Agent-Assisted Development
  9. Cost and Scale Estimation
  10. Detailed Topics
  11. Choosing Single vs Multi-Agent Architecture
  12. Architectural Reduction
  13. Iteration and Refactoring
  14. Practical Guidance
Ships with 3 files
  • references/case-studies.md
  • references/pipeline-patterns.md
  • scripts/pipeline_template.py
More from open-agent-hub
All skills →
About this skill
What does the project-development skill do?

This skill should be used for project-level decisions about LLM-powered systems: whether an LLM is the right primitive for the task at hand, the shape of a multi-stage batch or agent pipeline, token and cost estimation, choosing between single-agent and multi-agent at the project level, structured output design for downstream parsing, and structuring agent-assisted iteration. Use this when the unit of work is a whole project or a multi-stage pipeline. Route individual tool design to tool-design and individual skill-loading or context-budget tactics to context-optimization.

How do I install it?

Run `npx skills add guanyang/open-agent-hub --skill project-development --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From guanyang/open-agent-hub, a repository with 940 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going