Agent Skills for Context Engineering is a collection of reusable instructions that teach AI agents how to manage their context, coordinate multi-agent systems, and evaluate behavior. Developers use it when building or debugging production agent systems, and the catalogue entries are skills, agents, instructions, and a plugin from this collection.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add muratcankoylan/Agent-Skills-for-Context-Engineering --skill project-developmentgit clone --depth 1 https://github.com/muratcankoylan/Agent-Skills-for-Context-EngineeringWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/muratcankoylan/agent-skills-for-context-engineering/project-development)<a href="https://agentmods.dev/skills/muratcankoylan/agent-skills-for-context-engineering/project-development"><img src="https://agentmods.dev/badge/skills/muratcankoylan/agent-skills-for-context-engineering/project-development.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00111 | $0.03655 |
| Opus 5 | $0.00056 | $0.01827 |
| Sonnet 5 | $0.00022 | $0.00731 |
| Haiku 4.5 | $0.00011 | $0.00365 |
Grade A, and why
project-development scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
2 near-identical copies found in the catalogue:
- project-development — 100% identical, 2 lines differ
- project-development — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 305 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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 project level.
- Structuring agent-assisted iteration (where the agent helps build the project itself).
- Designing structured output at the pipeline contract level (cross-stage handoff format).
Do not activate this skill for adjacent work owned by other skills:
- Per-tool description, schema, naming, response format, error message:
tool-design. - Per-trajectory token-efficiency tactics (masking, partitioning, caching):
context-optimization. - Deciding to split work across sub-agents at the agent topology level:
multi-agent-patterns. - Designing the autonomous control loop (locked metrics, novelty gates, human approval boundaries):
harness-engineering.
Core Concepts
Task-Model Fit Recognition
Evaluate task-model fit before writing any code, because building automation on a fundamentally mismatched task wastes days of effort. Run every proposed task through these two tables to decide proceed-or-stop.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 305 lines · 111 tokens per session scan A acfeda3048cf
project-development is a skill published in the GitHub repository muratcankoylan/Agent-Skills-for-Context-Engineering (17,943 stars, last pushed 20d ago), licensed MIT. It adds 111 tokens to every session and 3,655 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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