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 agentmods add agents/daffy0208/ai-dev-standards/agentgit clone --depth 1 https://github.com/daffy0208/ai-dev-standardsWhat 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 | $0.00000 | $0.02643 |
| Opus 5 | $0.00000 | $0.01321 |
| Sonnet 5 | $0.00000 | $0.00529 |
| Haiku 4.5 | $0.00000 | $0.00264 |
Grade A, and why
AGENT 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 2d 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 — 433 lines — stays where its author put it; the contents beside it link to each section on GitHub.
What Are Agents?
Definition
An agent is an autonomous AI system that can perceive its environment, make decisions, and take actions to achieve specific goals. In the context of AI development, agents are specialized AI entities that:
- Perceive - Understand the current state of a task or problem
- Reason - Apply domain knowledge to determine the best approach
- Act - Execute tools, make decisions, and produce outputs
- Learn - Improve performance based on feedback and results
Types of Agents
1. Task-Oriented Agents
Execute specific, well-defined tasks with clear inputs and outputs.
Examples:
- Code review agent
- Test generation agent
- Documentation writer agent
- Bug finder agent
When to use:
- Single-purpose automation
- Repeatable workflows
- Quality assurance tasks
- Code analysis operations
2. Skill-Based Agents
Embody domain expertise and methodologies. Each agent represents a specialized capability.
Examples:
mvp-builder- Rapid product developmentrag-implementer- Retrieval-augmented generation systemsfrontend-builder- React/Next.js developmentsecurity-engineer- Security best practices
When to use:
- Domain-specific development
- Following established methodologies
- Applying specialized knowledge
- Complex multi-step workflows
3. Tool-Powered Agents
Agents that leverage MCP (Model Context Protocol) servers to extend their capabilities.
Examples:
- Agent with vector database tools (Pinecone, Weaviate)
- Agent with web scraping tools
- Agent with code analysis tools
- Agent with deployment tools
When to use:
- Need external tool integration
- API interactions required
- Database operations
- File system manipulations
4. Multi-Agent Systems
Coordinated groups of agents working together on complex problems.
Examples:
- Product team: strategist + designer + builder + tester
- RAG pipeline: chunker + embedder + retriever + generator
- CI/CD system: linter + tester + builder + deployer
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.
- 2d ago First seen · 433 lines · 0 tokens per session scan A c23c52a346ea
AGENT is an agent published in the GitHub repository daffy0208/ai-dev-standards (36 stars, last pushed 8mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,643 tokens. 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 agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
analyzer
Analyze blind comparison results to understand WHY the winner won and generate improvement suggestions.
grader
Evaluate expectations against an execution transcript and outputs.
comparator
Compare two outputs WITHOUT knowing which skill produced them.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.