Hire an AI nature project planner

Everything it can hand back

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

• Observation and small-trial teaching plan
• Learning record template and named stewardship handover

How it does the job well

• Start from the user problem and the evidence for it, then the solution.
• Write decisions down with the reason and the options you rejected.
• Keep scope small enough to ship and learn. Name what is out of scope.
• Define how success will be measured before building.

Mistakes it avoids

• Treating opinions or one loud request as proven demand.
• Specs that skip edge cases, error states or dependencies.
• Roadmaps with dates but no owners or confidence levels.

What a good result looks like

An example, not your task: Planning an early-years or primary local ecology inquiry

• Session table. Each session's question, observation, proposed action, adult gate, evidence and next decision.
• Baseline records and alternatives. What learners notice before any change, and options that do less.
• Adverse-effect watch points. What could go wrong for the place or its wildlife, and when to stop.
• Documentation sheet. Learner observations kept apart from adult interpretations, with consent-aware sharing rules.
• Care handover. A named owner and review date for ongoing care, or a note that stewardship is unresolved.
• Check table. PASS, FAIL or NOT RUN for each check, with missing inputs and assumptions listed.

How the work is checked

• Every requirement can be tested.
• Assumptions and risks are listed with how each will be checked.
• Dependencies and owners are named.
• 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

• Begin with the place. Use learners, site and observations to plan noticing, inquiry, a small trial, ongoing care and honest sharing. Pass the proposed action, local-system description and evidence gaps to impact review.
• Check effects before action. Use that system description and proposed action to test feasibility, unintended effects, adult responsibilities and doing less. Return revised action and stop conditions to documentation planning.
• Make learning and care visible. Use the revised inquiry to plan observations, learner explanations and reflection records. Separate direct observations from adult interpretations. Provide consent-aware sharing and future-care records.

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 plan-a-local-nature-project-with-stewardship 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/plan-a-local-nature-project-with-stewardship/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

• LEARNERS: give age group, access needs and adult supervision.
• PLACE: describe the site, permissions, seasonal limits and existing observations.
• PROJECT_LIMITS: give sessions, budget, allowed actions and who approves changes.
• RECORDING_RULES: state consent, photo privacy and learning-record sharing rules.

Functions and deliverables

• Plan a nature project that can continue: Describe a local place and learner group. Get an observation-led project, harm checks and a stewardship handover.
  • Observation and small-trial teaching plan
  • Learning record template and named stewardship handover
• Local nature inquiry cycle planner: Plan a term-long local nature inquiry for ages 5 to 12. Name a nearby place and get a five-stage cycle with activities, records and community links.
  • A cycle overview with the place at its centre
  • Activities for each stage
  • Ways to record and share learning
  • A list of community links to approach
  Source: Gareth Manning.
• Student systems change planner: Share a systems analysis and proposed action. Compare two or three options, possible side effects and what students can realistically influence.
  • Your action placed on the ladder of places to intervene
  • A list of likely side effects and delayed backlash
  • Two or three better or refined options
  • A ranking by impact
  Source: Gareth Manning.
• Reggio learning documentation planner: Describe children's activity and your purpose. Get a Reggio plan to record and share learning.
  • A capture plan for the activity
  • A format to share with families
  • Questions to interpret the evidence
  • Ideas for next steps
  Source: Gareth Manning.
• Product context file writer: Share product facts, audience and positioning. Get a reviewed context file that other marketing skills can reference.
  • A product marketing context file
  • A summary of what the file already holds
  • A change log of updates
  • Gaps you still need to fill
  Source: Corey Haines.

Tasks you can use it for

• Planning an early-years or primary local ecology inquiry
• You have the minimum inputs: the learners' age group, whether you have permission to use the site, and one adult who can approve actions. If you lack any of these, gather them first or use the plan for observation only.

Limits to check before starting

• You want a unit that teaches a set curriculum goal in one nearby place: use the Local nature inquiry unit planner.
• You only need outdoor lessons with a safety plan: use the Outdoor lesson sequence planner.
• You have no site permission or adult supervision yet: use the plan as a desk or classroom observation plan, and do not plant, move wildlife or change the habitat.

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.

• Download the complete workflow or agent pack and unzip it.
• Give the complete folder to your AI. Start with START_HERE.txt, then provide the named inputs in the coordinator skill.
• Follow its checkpoints and check the evidence before using any output. Agent packs run one requested cycle; they do not create a schedule.

Read it as data

Read the complete role setup as JSON. Connect your AI to the AI Blocks MCP library and read aiblocks://roles/plan-a-local-nature-project-with-stewardship 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.