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 nWave-ai/nWave --skill nw-agent-creation-workflowgit clone --depth 1 https://github.com/nWave-ai/nWaveWrote 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/nwave-ai/nwave/nw-agent-creation-workflow)<a href="https://agentmods.dev/skills/nwave-ai/nwave/nw-agent-creation-workflow"><img src="https://agentmods.dev/badge/skills/nwave-ai/nwave/nw-agent-creation-workflow.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Rogue Agent · line 52 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
- medium Agent Snooping · line 103 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00024 | $0.01700 |
| Opus 5 | $0.00012 | $0.00850 |
| Sonnet 5 | $0.00005 | $0.00340 |
| Haiku 4.5 | $0.00002 | $0.00170 |
Grade A, and why
nw-agent-creation-workflow 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 8d 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.
How it starts
The opening of the file, as written. The whole thing — 176 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Creation Workflow
Overview
Create agents through 5 phases: ANALYZE -> DESIGN -> CREATE -> VALIDATE -> REFINE. Each phase has clear inputs, outputs, and quality gates. Follow "start minimal, add based on failure."
Phase 1: ANALYZE
Goal: Understand requirements and determine agent architecture.
Inputs: User requirements, use case description, existing codebase context.
Steps:
- Identify single clear responsibility
- Determine new agent or modification of existing
- Check overlap with existing agents (avoid duplication)
- Classify agent type:
- Specialist: Single-domain expert (most common)
- Reviewer: Validates outputs from another agent (Reflection pattern)
- Orchestrator: Coordinates multiple agents
- Identify required tools (start with Read, Glob, Grep -- add only what's needed)
- Determine if Skills needed (domain knowledge > 50 lines)
Gate: Single responsibility identified. Agent type classified. No overlap.
Output: Requirements summary with agent type, tools list, skill needs.
Phase 2: DESIGN
Goal: Design agent architecture and structure.
Inputs: Requirements summary from Phase 1.
Steps:
- Select design pattern (load
design-patternsskill) - Define role and goal (1-2 sentences each)
- Identify core principles that DIVERGE from Claude defaults:
- What must this agent do differently than Claude naturally would?
- Domain-specific methodology steps
- Non-obvious constraints | Project-specific conventions
- Design workflow (3-7 phases)
- Plan Skills extraction: domain knowledge -> separate Skill | Testing/validation -> separate Skill | Keep workflow and principles in core agent
- Design Skill Loading Strategy (required for 3+ skills):
- Map each skill to the workflow phase where it's needed
- Create a loading table: Phase → Skill → Trigger condition
- Add explicit
Load: skill-namedirectives in each workflow phase - Document path:
~/.claude/skills/nw-{skill-name}/SKILL.md(installed) ornWave/skills/nw-{skill-name}/SKILL.md(repo) - Note:
skills:in frontmatter is declarative only — Claude Code does NOT auto-load skill files. The agent must use Read tool to load them, triggered byLoad:directives in workflow text.
- Draft frontmatter:
--- name: {kebab-case-id} description: Use for {domain}. {When to delegate.} model: inherit tools: [{minimum tools needed}] maxTurns: 30 skills: - nw-{skill-name} ---
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.
- 8d ago First seen · 176 lines · 24 tokens per session scan A 98a9ef586280
nw-agent-creation-workflow is a skill published in the GitHub repository nWave-ai/nWave (608 stars, last pushed 2d ago), licensed MIT. It adds 24 tokens to every session and 1,700 once invoked, about $0.0001 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.
Other skills, from other repositories
workflow-patterns
Use this skill when implementing tasks according to Conductor's TDD workflow, handling phase checkpoints, managing git commits for tasks, or understanding the verification protocol.
engineering-workflow
A Chinese-language workflow for reliable software development. It describes exploring the problem, making a plan, using TDD (test-driven development, where tests are written before the code), debugging methodically, reviewing code, and verifying the result.
test-driven-development
Strict RED-GREEN-REFACTOR cycle enforcement. Tests are never skipped or deferred. Run mode only, never watch mode. Exit code evidence mandatory.
tdd-enforcement
Red-Green-Refactor TDD methodology with mandatory failing tests, minimal implementation, quality refactoring, and 80% coverage gating.
story-development
Implement user stories with test-driven development methodology.
tdd
A Test-Driven Development guide. TDD means writing a failing test first, adding the smallest implementation that passes it, and then improving the code while keeping the tests passing.