project-development
Guides project-level decisions for LLM systems: task fit, pipeline shape, token and cost estimates, single or multi-agent design and structured output.
- Kind
- Skill
- Works with
- Any agent
- Source
- Agent Skills for Context Engineering @ 9ff0c99108b3
- Path
- skills/project-development/SKILL.md
- Jobs
- Planning
- Topics
- LLM apps & RAG, Agents & MCP
Credit
- Made by
- muratcankoylan
- Original
- github.com/muratcankoylan/Agent-Skills-for-Context-Engineerin…
- License
- MIT
Listed by Skill Manifest; not made by us.
InstallInstall it from a plugin marketplace.
/plugin install context-engineering@context-engineering-marketplace
Install factsScanned 2 Nov 2026
- Adds
- .claude/skills/project-development/ (the skill folder)
- 2 file(s) the skill refers to
- Runs scripts
- None found
- Uses the network
- None found
- Needs secrets
- None found
- Source revision
- 9ff0c99108b3
- Licence
- MIT
- Last activity
- 12 Oct 2026
- Review
- Reviewed
Found by a static scan of the stored text; nothing is run. “None found” is not a guarantee, so read what you install before you run it.
- Only the main file is read; other files in the folder are not scanned
# 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. …