Home / vasilyu1983 / ai-agents-public · frameworks/shared-skills/skills/ai-agents/SKILL.md · GitHub

ai-agents skillA

ai-agents is agent-read markdown (skill) from vasilyu1983/ai-agents-public: AI agent architecture, graph and loop composition, protocol choice, evaluation, and observability. Use when scoping or reviewing systems before implementation..

Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.

What the file says

# AI Agents Development — Architecture Hub

Use this skill to decide whether a workflow should be an agent, which agent shape fits, which protocol boundary to use, and what production controls must exist before rollout.

Default posture: explicit control flow, bounded tools, typed contracts, auditable state, human approval for high-risk actions, and telemetry from day one.

Keep this file lean. Load detail from [`references/index.md`](references/index.md), `assets/`, and sibling skills only when needed.

## When to Use This Skill

Use this skill when the user asks for:

- agent architecture or operating-model decisions
- build-vs-not-agent assessment
- MCP vs A2A protocol choice
- production readiness review for an existing agent system
- evaluation, observability, rollout, or safety planning
- framework selection after requirements are already clear
- a starting template for a new agent spec
- graph engineering, agent/workflow graphs, state-machine orchestration, cyclic graphs, or DAG-versus-loop design
- loop engineering, run-until-done coding agents, self-improving workflows, evaluator feedback loops, or bounded autonomous iteration
…

Read the whole file at its exact version.

How to install

Latest version
mdr add vasilyu1983/ai-agents-public/ai-agents@v1.1
Exact content
mdr add vasilyu1983/ai-agents-public/ai-agents@sha256:a8aab55246551156

Pin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.

Badge

mdr badge

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Versions

versioncommittedcommitsizeaudit
v1.1 latest2026-09-23 8dc5de4 23,545 BA view · diff
v1.12026-08-21 53f6cb7 22,934 BA view · diff
v1.12026-08-09 da9d28f 21,984 BA view

Audit of the latest version

A  17 of 17 checks passed. Deterministic, no model, same answer every run.
  • pass: Frontmatter block present
  • pass: Frontmatter declares a name
  • pass: Frontmatter declares a description
  • pass: Size between 200 bytes and 200 KB (23545 bytes)
  • pass: No zero-width or bidi control characters
  • pass: No instruction hidden inside an HTML comment
  • pass: No link to an exfiltration or paste host
  • pass: No credential-shaped string
  • pass: No instruction to send local credentials anywhere
  • pass: No text hidden with inline styles
  • pass: No prompt-injection phrasing
  • pass: No curl or wget piped into a shell
  • pass: No recursive delete of root, home or parent
  • pass: No instruction to read or print local credentials
  • pass: No base64 blob over 200 characters
  • pass: No link to a raw IP address
  • pass: No script tag

Source

GitHub

vasilyu1983/ai-agents-public · 88 stars · license MIT · pushed 2026-09-23 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_abuw23qpgsg6z7je
GET https://markdownregistry.com/api/v1/resolve?ref=vasilyu1983/ai-agents-public/ai-agents
GET https://markdownregistry.com/api/v1/blob/a8aab552465511569f427ea617afa6117d0380781eccd0021daf4f95e987ff11

Your agent does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.

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