agent-development

A guide for designing and building AI agents that use tools, remember information, plan work, coordinate with other agents, and follow safety limits.

In plain words
What is it for?
Use it to design agent loops, memory, tool access, multi-agent workflows, evaluations, and safety guardrails.
Why use it?
It helps turn an agent idea into an observable, testable design with clear boundaries before implementation begins.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/pixel-process-ug/superkit-agents/agent-development
Any agent
npx skills add Pixel-Process-UG/superkit-agents --skill agent-development
Clone the repo
git clone --depth 1 https://github.com/Pixel-Process-UG/superkit-agents

Made for: Claude Code, Codex.

Per session 71 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,437 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00071 $0.02437
Opus 5 $0.00036 $0.01218
Sonnet 5 $0.00014 $0.00487
Haiku 4.5 $0.00007 $0.00244

Measured 2d ago against content hash 4a5656d6d471, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

agent-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 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.

templates/skills/agent-development/SKILL.md · 313 lines

How it starts

The opening of the file, as written. The whole thing — 313 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Agent Development

Overview

Design and build AI agents that effectively use tools, manage memory, plan multi-step tasks, coordinate with other agents, and operate within safety guardrails. This skill covers the full agent development lifecycle from architecture through evaluation, with emphasis on observable, testable, and safe agent behavior.

Phase 1: Agent Design

  1. Define the agent's purpose and scope
  2. Identify required tools and capabilities
  3. Design memory architecture (short-term, long-term)
  4. Plan agent loop structure (observe, think, act)
  5. Define safety boundaries and guardrails

STOP — Present agent design to user for approval before implementation.

Agent Architecture Decision Table

Agent Type When to Use Loop Pattern Complexity
Single-turn tool user Simple queries with tool calls Request -> Tool -> Response Low
ReAct agent Multi-step reasoning tasks Thought -> Action -> Observation -> loop Medium
Plan-and-execute Complex tasks with dependencies Plan -> Execute steps -> Validate Medium-High
Multi-agent orchestrator Parallel/specialized sub-tasks Dispatch -> Collect -> Synthesize High
Autonomous loop (Ralph-style) Long-running iterative development Plan -> Build -> Verify -> Exit gate High

Phase 2: Implementation

  1. Build the agent loop with tool dispatch
  2. Implement memory management (context window, persistence)
  3. Add planning and decomposition logic
  4. Integrate error recovery and retry patterns
  5. Implement output validation

STOP — Run smoke tests on the agent loop before adding complexity.

Tool Use Patterns

Tool Definition Best Practices
Principle Rule Example
Clear naming verb-noun format search_documents, create_file
Detailed descriptions Include when to use AND when NOT to use "Use for keyword search. Do NOT use for semantic similarity."
Well-typed parameters Descriptions and examples on every param query: string // "e.g., 'user authentication'"
Predictable returns Consistent format across tools Always return { success, data, error }
Self-correcting errors Help agent recover "Invalid date format. Expected ISO 8601: YYYY-MM-DD"

Read the full file on GitHub · 313 lines

Changes

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.

  1. 2d ago First seen · 313 lines · 71 tokens per session scan A 4a5656d6d471

Subscribe to this mod's changes

agent-development is a skill published in the GitHub repository Pixel-Process-UG/superkit-agents (1 stars, last pushed 5mo ago), licensed MIT. It adds 71 tokens to every session and 2,437 once invoked, about $0.0004 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 2026-08-31.

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