magnus919_agent-skills/bundles/workflow-architect/SKILL.md

name, description, license, compatibility, metadata

name	description	license	compatibility	metadata
workflow-architect	Discover your actual workflow through conversation or observation, then generate a tailored skills bundle that encodes it as loadable agent skills with trigger conditions. Use when you want to understand your own process, formalize it, or share it with collaborators. Also use when a session feels aimless — this skill gives it structure.	MIT	Hermes Agent — uses skill_view(), memory tool, session context scanning, and write_file for bundle generation. Output bundles are standard Agent Skills.	tags spec-version workflow, meta, productivity, skills-bundle, onboarding, process 1.0

Workflow Architect

A meta-skill that helps you (and your agent) understand how you actually work. It discovers your workflow patterns through either active interrogation or passive observation, then generates a skills bundle — a set of loadable skills, each with trigger conditions, that encode your workflow so your agent can meet you where you are in every session.

What You Get

After running workflow-architect, you'll have a new bundle in your agent's skill directory containing:

• Umbrella SKILL.md — the entry point that makes the bundle auto-detectable via trigger conditions in its description. Load it with skill_view(name='<bundle-name>') or let the agent discover it automatically when you say something matching its triggers.
• Sub-skills — one per phase of your workflow, each with a description that tells the agent when to load it (e.g., "load this when the user starts their morning triage routine" or "use this when the user shifts into deep work mode")
• A manifest — maps skill names to their trigger conditions, entry points, and transition signals
• A decision map — Mermaid flowchart visualizing your workflow as the agent sees it
• A kanban board (optional) — only included if your workflow follows a predictable linear path where WIP limits and lane transitions add value

The umbrella and sub-skills are registered via skill_manage(action='create') so they appear in skills_list() and are immediately loadable in future sessions.

Two Modes

Workflow-architect adapts to how you want to engage with it.

Mode 1: Active Interrogation (One-Shot)

When to use: You have a few minutes to talk through your process. This is the most thorough mode — the agent asks guided questions, branches based on your answers, and builds a model of your workflow turn by turn.

How to invoke:

/workflow-architect

The agent will guide you through a conversation of about 8-15 questions. Answer naturally — the skill adapts its probes based on what you say.

Mode 2: Passive Observation

When to use: You're already in a session doing real work and don't want to stop and reflect. Let this mode watch what you actually do, then infer the workflow pattern from your actions.

How to invoke:

/workflow-architect passive

The agent loads the observer skill silently. It does nothing until you say one of the trigger phrases below, at which point it scans the current session's message history and reconstructs your workflow from what happened.

Trigger phrases (say any of these to activate observation analysis):

• "catalog my workflow"
• "what's my workflow"
• "analyze my process"
• "figure out what I do"
• "work it out from what I just did"

Limitation: Observation mode works best after a session with at least 20+ turns of substantive work. If the session context is too thin, the observer will suggest switching to active interrogation mode instead.

Loading Protocol

1. Read this umbrella SKILL.md for context
2. If active: load skills/interviewer/SKILL.md
3. If passive: load skills/observer/SKILL.md
4. After convergence: load skills/bundle-builder/SKILL.md to synthesize and write the output bundle. The bundle is written to ~/.hermes/skills/<category>/<bundle-name>/ — verify the umbrella loads with skill_view(name='<bundle-name>') and at least one sub-skill loads with skill_view(name='<bundle-name>-<phase-name>'). Tell the user where it landed, what skills it contains, and a trigger phrase they can use to enter the workflow.

What the Interview Builds

The interviewer (and observer, through inference) builds a structured model with these dimensions:

Dimension	What it captures
Entry points	How your sessions typically start
Phases	The distinct modes or stages in your workflow
Branching signals	What makes you go left vs right at each fork
Tool preferences	What you reach for in each phase
Loop conditions	What keeps you in a mode vs what kicks you out
Exit criteria	How you know a session is done
Pain points	What feels frictionful or inefficient

Environment

No environment variables required. State is stored via memory tool with the prefix workflow-architect:state: so it persists across turns during multi-turn interviews.