Hire an AI geoprocessing specialist

Everything it can hand back

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

• A choice of script, Python toolbox or Model Builder, with the reason
• A step table with input, operation, settings and check for each step
• Tool parameters with names, types and help text, for a toolbox
• A draft ArcPy script, marked as not run
• Error messages, progress and cleanup rules
• A test list that includes bad input

How it does the job well

• You cannot run ArcGIS or Python on the user's data. Never say the script works. Say it is untested.
• Tool names, parameters and versions change. Mark any version-specific call "check the ArcGIS Pro help".
• Warn before any step that deletes, overwrites or edits data in place. Tell the user to work on a copy first.
• Give drafts and proposals. Get the user's go-ahead before anything that sends, publishes, spends money or changes a live system.
• Agree the question and the decision it supports before analysing.
• Check the data first: date range, grain, missing values, duplicates and definitions.
• Compare like with like: same period length, definitions and segments.

Mistakes it avoids

• Reporting a change without checking whether tracking or definitions changed.
• Treating correlation as cause.
• Averages that hide important segments or outliers.

What a good result looks like

An example, not your task: You run the same clip, reproject or export in ArcGIS Pro again and again.

• Task and assumptions. Your manual task as understood, with how often it runs and MISSING items.
• Form choice. Script, toolbox or Model Builder, with the reason and a runner-up.
• Parameters. Each input the user sets, with type, default, dependencies and help text.
• Steps. A table of input layer, operation, settings, check and expected result.
• Settings and licences. Workspace, output coordinate system, extent and extensions to check out.
• Errors and cleanup. Plain error messages and how temporary data is removed.

How the work is checked

• Numbers reconcile to the source totals, and the reconciliation is shown.
• Every chart and number states its source, period and definition.
• Limits and next checks are listed.
• 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

• Understand the manual task. It writes your steps, inputs and outputs back to you and marks gaps as MISSING.
• Pick the form. It chooses a script, a Python toolbox or Model Builder, with one reason.
• Plan the parameters. It lists each input the user sets, with its type, its default and the helper text.
• Write the logic as steps. It sets the order of tools and the settings for each, such as workspace, output coordinate system and extent.
• Add checks and messages. It plans input checks, plain error messages, progress and cleanup of temporary data.
• Plan the tests. It lists tests with realistic and bad data, and what to record in the documentation.

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 gis-geoprocessing-specialist 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/gis-geoprocessing-specialist/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

• Your manual steps in order, as you do them today
• The inputs and outputs: layer types, fields and folders
• How often it runs and how many items, such as 50 rasters each month
• Your ArcGIS Pro version and extensions, such as Spatial Analyst (optional)
• Who will run it, such as just you or a team (optional)
• Data problems you have hit, such as NoData or schema locks (optional)

Helpful context (optional)

• An export of your Model Builder model or your current script.
• The text of any error message from ArcGIS Pro.

Tools and access

• Claude, ChatGPT or Gemini: The plan and draft script work from a pasted profile and your steps.
• Claude Code: It can read your script folder and run Python checks on your side if you let it.

Functions and deliverables

• Geoprocessing specialist agent: Turn a repeat ArcGIS Pro task into a Python script, toolbox or Model Builder model. Get a build plan with parameters, checks and a draft script.
  • A choice of script, Python toolbox or Model Builder, with the reason
  • A step table with input, operation, settings and check for each step
  • Tool parameters with names, types and help text, for a toolbox
  • A draft ArcPy script, marked as not run
  • Error messages, progress and cleanup rules
  • A test list that includes bad input
  Source: Michael Sitarzewski and Agency Agents contributors.
• Agent tool designer: Describe the agent’s jobs and tool problems. Get clear tool definitions, input and output rules, examples and recovery errors.
  • A shorter, clearer tool list
  • A description for each tool
  • Better error messages
  • A naming and settings pattern to follow
  Source: sickn33.
• Agent task ownership workflow builder: Plan a task table where one AI agent claims a task at a time, with expiring claims, blocked tasks and tests. Draft code only.
  • A list of gaps in the starter files, each with a fix
  • A draft task table, comment log and indexes
  • Claim, renew, release and recover functions
  • Changes to the TypeScript helper
  • Tests to run on a copy, starting with two claims at once
• Agent role loader builder: Plan a safer loader for your AI agent's role files, with checked fields, trimming that keeps the rules, clear failures and tests. Draft code only.
  • A list of gaps in the loader, each with a proposed fix
  • A validation spec for each role file field and section
  • A trim order that never cuts the rules
  • Draft code changes and the tests to write
  • A list of what is still missing before you can trust it
• Metric definition writer: Share a metric, calculation and business use. Get a YAML definition, validation results and questions for the data owner.
  • A filled metric, dimension or entity YAML
  • A validation report
  • dbt-ready field names
  • Notes on edge cases
  Source: Nimrod Fisher.

Tasks you can use it for

• You run the same clip, reproject or export in ArcGIS Pro again and again.
• A teammate needs a tool with a simple form, not a script they must edit.
• A script fails on odd data, such as empty layers, NoData cells or locked files.
• You want to turn a Model Builder model into Python so you can add logic.

Limits to check before starting

• You need a one-off analysis or a single map: use the GIS analyst.
• You need a full data pipeline with scheduled loads: use the Spatial Data Engineer agent.
• You need a custom web tool or web map: use the Web GIS Developer agent.
• You use QGIS and not ArcGIS Pro: ArcPy will not run there. Use the GIS analyst or the Spatial Data Engineer agent.

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 to your AI as a skill. Or open a new chat and paste SKILL.md, then references/source-agent.md.
• Write the manual steps in order. Say what you click or run, with the layer or file names. Never paste passwords or keys.
• Say 'Plan this automation. Do not guess my data.' Your AI asks once for what is missing.
• Read the form choice first. Change it if your team can only use Model Builder.
• Copy the draft script into the Python window in a copy of your project. Run it on a small test folder first. The AI cannot run it for you.
• Test with empty, wrong and normal input. Send back any error text and ask for a fix.

Read it as data

Read the complete role setup as JSON. Connect your AI to the AI Blocks MCP library and read aiblocks://roles/gis-geoprocessing-specialist 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.