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 tool-designgit 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/tool-design)<a href="https://agentmods.dev/skills/muratcankoylan/agent-skills-for-context-engineering/tool-design"><img src="https://agentmods.dev/badge/skills/muratcankoylan/agent-skills-for-context-engineering/tool-design/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/muratcankoylan/agent-skills-for-context-engineering/tool-design"><img src="https://agentmods.dev/badge/skills/muratcankoylan/agent-skills-for-context-engineering/tool-design.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00109 | $0.03850 |
| Opus 5 | $0.00055 | $0.01925 |
| Sonnet 5 | $0.00022 | $0.00770 |
| Haiku 4.5 | $0.00011 | $0.00385 |
Grade A, and why
tool-design 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 10d 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
3 near-identical copies found in the catalogue:
- tool-design — 100% identical, 0 lines differ
- tool-design — 100% identical, 0 lines differ
- agent-tool-design — 94% identical, 8 lines differ
How it starts
The opening of the file, as written. The whole thing — 297 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Tool Design for Agents
Design every tool as a contract between a deterministic system and a non-deterministic agent. Unlike human-facing APIs, agent-facing tools must make the contract unambiguous through the description alone: agents infer intent from descriptions and generate calls that must match expected formats. Every ambiguity becomes a potential failure mode that no amount of prompt engineering can fix.
The unit of work for this skill is a single tool or a tool catalog. Project-shape, pipeline architecture, task-model-fit, and cost-at-the-project-level decisions belong to project-development. Deciding whether to introduce sub-agents belongs to multi-agent-patterns. This skill owns the interface layer that connects deterministic code to the agent.
When to Activate
Activate this skill when the unit of work is a tool:
- Writing a new tool description, schema, or response format.
- Debugging cases where the agent picked the wrong tool or generated malformed calls.
- Consolidating an overlapping tool catalog (the classic "we have 17 tools, the agent picks wrong half the time" case).
- Designing actionable error messages so the agent can self-correct.
- Naming tools and parameters consistently across a catalog (MCP namespacing, verb-noun naming).
- Evaluating a third-party tool against the consolidation principle before adding it.
Do not activate this skill for adjacent work owned by other skills:
- Deciding whether the project should use LLMs at all, or what the pipeline stages should be:
project-development. - Deciding whether to split work across sub-agents or run a single agent with more tools:
multi-agent-patterns. - Reducing the token weight of tool outputs at the trajectory level (observation masking, format-option choice at scale):
context-optimization.
Core Concepts
Design tools around the consolidation principle: if a human engineer cannot definitively say which tool should be used in a given situation, an agent cannot be expected to do better. Reduce the tool set until each tool has one unambiguous purpose, because agents select tools by comparing descriptions and any overlap introduces selection errors.
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.
- 10d ago First seen · 297 lines · 109 tokens per session scan A 14f5a12b6911
tool-design is a skill published in the GitHub repository muratcankoylan/Agent-Skills-for-Context-Engineering (17,947 stars, last pushed 21d ago), licensed MIT. It adds 109 tokens to every session and 3,850 once invoked, about $0.0005 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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