Hire an AI workflow specification writer

Everything it can hand back

Your task sets the actual outputs. The specialist picks the methods that cover them.

• A workflow spec with the steps, each with time limit, input, success output and failure branches
• A list of what the customer, the operator and the database show at each step
• A cleanup path that undoes partial work, with a list of everything created
• A table of handoffs between systems, with the data, success reply, failure reply and time limit
• A test case for every branch
• A list of assumptions and open questions that need a person to answer

How it does the job well

• One workflow per spec. Mention related ones, but do not fold them in.
• No happy-path-only specs. Every step has failure branches and a timeout.
• No undefined handoffs. Every boundary has a payload, a success reply, a failure reply, a timeout and a recovery action.
• Flag timing assumptions. Any step that needs something else to be ready is a possible race. Name the thing that guarantees the order, or log it as an assumption.
• No implementation choices. Say what must happen, not how the code does it.
• Turn every request into owned actions: who, what and by when.
• Work from the real calendar, notes and lists. Never invent meetings, people or dates.

Mistakes it avoids

• Losing commitments buried in long notes.
• Mixing confirmed facts with guesses about other people's plans.
• Adding process when a short checklist would do.

What a good result looks like

An example, not your task: You are about to build a feature with several steps or systems, such as signup, checkout or account deletion.

• Overview, actors and trigger. What the workflow does, who is in it, what must be true first and what starts it.
• Workflow tree. Each step with its time limit, input, outputs, failure branches and what each party sees.
• Cleanup path and inventory. How partial work is undone, and a list of everything the workflow creates.
• Handoff contracts. For each system boundary, the data sent, success and failure replies and the time limit.
• Test cases. One test for every branch in the tree, with the trigger and the expected result.
• Assumptions and open questions. Everything the AI could not verify, with the risk if it is wrong.

How the work is checked

• Every action has an owner and a date, or is marked as missing one.
• Each item points to the note or message it came from.
• The output fits where it will be used, such as one screen or one page.
• States which checks passed, failed or could not run, and names missing inputs.

These checks have not been run against a model yet. Your AI uses them to check its own work.

Capabilities

• Find the facts. If you share code, it reads the routes, workers, schema and config for the workflow. It notes where the code differs from your description.
• List the actors. It names every system and person in the workflow, and what each one does.
• Map the happy path. It writes the steps from trigger to finished, with the data passed at each handoff.
• Branch every step. For each step it adds the time limit and every failure, with retry or stop rules and what was already created.
• Show what each party sees. It states what the customer, the operator, the database and the logs show at each step.
• Close out. It adds the cleanup list, the test cases, the assumptions and the open questions, and marks the spec Draft.

How the role works

1. Checks your task, context and available tools.
2. Picks the methods needed and prepares a work plan.
3. Carries out supported tasks, with each method's limits and review gates.
4. Checks the real deliverables and corrects supported faults.
5. Hands back files, evidence and unresolved gaps.

Your specialist's working setup

Download the base specialist without a task form or account. README.md and SETUP.md explain how to use the folder. SOUL.md defines its scope. INTAKE.md asks missing questions inside your AI. PLAYBOOK.md, SKILLS.md, BEST_PRACTICES.md, CHECKS.md and HANDOFF.md guide the work and its checked deliverables.

Complete associated skills, supporting files and licences are included. Choose only the methods needed for the actual task. Keep context, working files and accepted feedback in your AI project.

Use this specialist through MCP or the API

Call prepare_specialist with role_id specialized-workflow-architect only. No task is required to load it. Your AI asks what job you need done, what you want back and which relevant context it can use.

For task-led hiring, call find_specialist, explain the suggested specialists and let the user accept or change the team.

Complete ZIP: Download base specialist. API: GET /api/v1/specialists/specialized-workflow-architect/pack. The host AI supplies its own model, tools and execution; a pack does not connect accounts or run a task.

Inputs and helpful context

The specialist starts from the task brief. Only active methods require their inputs.

For the primary method, when used

• The workflow to spec, with its name, what starts it and the result you want
• The systems and people involved, such as the app, a payment service and an admin
• Code, routes, a database schema, config or design notes, if you have them (optional)
• Failures you already know about, or fear (optional)
• Time limits or service targets for the workflow (optional)

Helpful context (optional)

• The tickets or incident notes from past failures of this workflow.
• A list of the services it calls, with any time limits they publish.

Tools and access

• Claude Code or Codex: They can read your routes, workers and schema, so the spec matches the real code and not just your description.
• Claude, ChatGPT or Gemini: They can write the spec from your notes, but every unverified step lands in the assumptions list.

Functions and deliverables

• Workflow specification writer: Turn a feature into a workflow spec with every path, failure, cleanup and test case written down before anyone builds it.
  • A workflow spec with the steps, each with time limit, input, success output and failure branches
  • A list of what the customer, the operator and the database show at each step
  • A cleanup path that undoes partial work, with a list of everything created
  • A table of handoffs between systems, with the data, success reply, failure reply and time limit
  • A test case for every branch
  • A list of assumptions and open questions that need a person to answer
  Source: Michael Sitarzewski and Agency Agents contributors.
• AI creative workflow handoff planner: List the steps in your creative AI workflow. Get clear instructions for passing facts and results between them, with claim limits kept intact.
  • Claim cards, each with its full wording, limits and source
  • A handoff card for each step (needs, may use, returns, never lose)
  • A bundle order (stable part first, then the part that changes) and run rules
  • A list of shortfalls and trade-offs
  • Any of its own checks the plan still misses, each named
• Workflow spec interviewer: Share the workflows you want to build. It asks focused questions and writes a clear spec for each one.
  • One spec file per workflow
  • Trigger and checkpoint for each
  • Notes file on your tools and terms
  • List of open questions until done
  Source: Matt Pocock.
• Pay raise case builder: Share your results and the pay raise you want. Get your case, a script and replies to likely answers.
  • Your results, sorted by what matters to your manager
  • A list of pay evidence to look up before you go in
  • Your ask as a range, with one number you would take
  • A short script, replies to likely answers, and other things to ask for
• me.md builder: Answer a few questions, or let your AI use what it remembers. Get one private file that tells any AI who you are.
  • One me.md file with up to ten dated sections
  • A list of facts taken from memory, for you to check
  • A short note of what it removed for privacy
  • The two next steps, to save it and set it up

Tasks you can use it for

• You are about to build a feature with several steps or systems, such as signup, checkout or account deletion.
• A flow fails midway in production and leaves half-created records, and you want the full set of paths written down.
• You hand a feature to a developer or a testing team and want them to stop asking what happens if it fails.
• You inherited a system and want to find the workflows that exist in the code but have no spec.

Limits to check before starting

• You want to design how several AI agents hand work to each other. Use the AI agent workflow designer.
• You want an automation laid out in n8n. Use the n8n workflow designer.
• The process is a business process with people and paperwork, not software. Use the Operations Manager agent.
• You want a short task plan for a coding change. Use the Coding task planner.

Best way to use this role

Give it one clear outcome, the actual files and a definition of done. Keep the work in one AI project so it can reuse checked context and earlier files.

• Add the pack as a skill, or paste SKILL.md and then references/source-agent.md into a new chat.
• Name one workflow and say what starts it. Paste or upload any code, routes or notes. Say who the actors are.
• Run it once for one workflow. If the AI spots a related workflow, it will name it and leave it for the next run.
• Read the assumptions and open questions first. Answer them, or send them to the engineer who knows.
• Check the spec against the real code. Mark what matches and what does not. Do not approve a spec that nobody has compared with the code.
• Give the spec to the developer and give the test case table to whoever tests.

Read it as data

Read the complete role setup as JSON. Connect your AI to the AI Blocks MCP library and read aiblocks://roles/specialized-workflow-architect for its role instructions and pinned sources.

This is a prepared AI role. No task has run. Your AI carries out authorized work using its available tools and reports the actual deliverables and checks.