Agent-Skills.md

Agent Skills: Session-to-Agent Skill

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UncategorizedID: rysweet/amplihack/session-to-agent

Repository

rysweet/amplihack
rysweet
4124

Install this agent skill to your local

pnpm dlx add-skill https://github.com/rysweet/amplihack/tree/HEAD/amplifier-bundle/skills/session-to-agent

Skill Files

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amplifier-bundle/skills/session-to-agent/SKILL.md

Skill Metadata

Name
session-to-agent
Description
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Session-to-Agent Skill

Convert an interactive coding session into a reusable goal-seeking agent with memory. The skill reads session transcripts, extracts goals and patterns, and generates a complete agent via amplihack new.

Quick Start

Step 1: Invoke the skill

User: /session-to-agent

Or describe what you want:

User: Turn this session into a reusable agent

Step 2: The skill extracts from the current session

It analyzes the session transcript to identify:

  • Primary goal and sub-goals
  • Constraints (technical, operational, time)
  • Tools and commands used
  • Patterns and strategies observed
  • Domain knowledge gained during the session

Step 3: A goal-seeking agent is generated

The skill writes a prompt.md file and runs:

amplihack new --file prompt.md --sdk copilot --enable-memory

The generated agent can be re-run autonomously to repeat or extend the session's workflow.

What It Extracts

| Category | Examples | | -------------------- | ---------------------------------------------------- | | Primary Goal | "Implement JWT authentication for the REST API" | | Sub-Goals | Token generation, middleware, refresh flow, tests | | Constraints | Must use RS256, tokens expire in 1h, no external IdP | | Tools Used | pytest, ruff, git, curl, Bash, Read, Edit | | Patterns | Outside-in TDD, error-first validation, retry logic | | Domain Knowledge | JWT spec details, library quirks, API contract rules | | Success Criteria | All tests pass, CI green, security review approved |

Customizing the Generated Agent

After generation, you can refine the agent by editing:

  • prompt.md -- the goal description and constraints
  • plan.yaml -- the execution phases and dependencies
  • skills.yaml -- the required skills and tool mappings
  • metadata.json -- SDK, memory, and multi-agent settings

Re-run the generator after edits:

amplihack new --file prompt.md --sdk copilot --enable-memory

Memory Export (Optional)

When --enable-memory is used, the skill can optionally export the current session's Kuzu memory database as the agent's initial knowledge base. This seeds the new agent with facts, discoveries, and context from the session that created it.

# Export is offered interactively after agent generation
# Or specify explicitly:
amplihack new --file prompt.md --enable-memory --sdk copilot

When to Use This Skill

  • After completing a multi-step workflow you want to repeat
  • When a session reveals a reusable process worth automating
  • To hand off a workflow to a colleague as a runnable agent
  • To create a CI/CD or SRE automation agent from manual steps
  • When session knowledge should persist as an executable artifact

When NOT to Use This Skill

  • For trivial single-command tasks (use a script instead)
  • When the session was exploratory with no clear repeatable goal
  • When the workflow is already captured as a recipe or agent

Supporting Files

| Need | File | | --------------------------------------- | -------------------------------- | | Full extraction algorithm and templates | reference.md | | Worked examples with real sessions | examples.md | | Goal-seeking agent design guidance | goal-seeking-agent-pattern skill | | Knowledge extraction from sessions | knowledge-extractor skill |