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ai-agent-engineering

Use to specify, build or review AI agents, LangGraph or LangChain systems, RAG, tool calling, memory, structured extraction, multi-agent workflows…

Skill by SiddheshKGupta

IndexedApache-2.0★ 4
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/siddheshkgupta-ai-agent-engineering

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

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About

Use to specify, build or review AI agents, LangGraph or LangChain systems, RAG, tool calling, memory, structured extraction, multi-agent workflows, evaluations, human approval and agent deployment. Do not deploy a catalogue blueprint without validating the exact repository.

Use cases: devops, ml, agent-building

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Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

Tools
No tools found
Secrets
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Install scripts
None found

Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/ai-agent-engineering

What's inside

Skill name
ai-agent-engineering
Description
Use to specify, build or review AI agents, LangGraph or LangChain systems, RAG, tool calling, memory, structured extraction, multi-agent workflows, evaluations, human approval and agent deployment. Do not deploy a catalogue blueprint without validating the exact repository.
License
Apache-2.0
Instructions
24 lines in SKILL.md · view on GitHub

Files (1)

  • SKILL.md

SKILL.md (first lines)

# AI Agent Engineering

Define:

```text
Outcome | Users | Model role | Inputs | State | Memory | Tools
Knowledge | Orchestration | Human approval | Guardrails | Evaluation
Observability | Cost | Privacy | Failure handling | Deployment
```

1. Decide whether an agent is necessary; prefer deterministic software for
   deterministic work.
2. Define the agent boundary and allowed autonomy.
3. Use explicit schemas for state, tools and outputs.
4. Separate retrieval, reasoning, action and verification.
5. Apply least privilege and human approval to sensitive actions.
6. Design retries, idempotency, timeouts and fallbacks.
7. Build task-specific evaluations before production use.
8. Record model, prompt, tool, data and version lineage.
9. Monitor quality, latency, cost, failures and unsafe behaviour.

An impressive demo is not production readiness.

From SiddheshKGupta/Escapement, Apache-2.0.

More from SiddheshKGupta/Escapement

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    Stars
    4
    Forks
    1
    Open issues
    0
    Last commit (this folder)
    Aug 5, 2026 (2 months ago)

    From GitHub (fetched Oct 24, 2026).

    Details

    License
    Apache-2.0
    Repository
    github.com/SiddheshKGupta/Escapement
    First seen
    Oct 24, 2026
    Last checked
    Oct 24, 2026
    Source
    GitHubgithub-graphql

    More from SiddheshKGupta

    Cite this page

    ai-agent-engineering skill. Agent Mart. https://agentmart.dev/skills/siddheshkgupta-ai-agent-engineering (last updated 2026-10-24)