Open scripts
AI-assisted drafting for G←O←S←R stages.
GOSR AI Workflow →The GOSR Method
A minimal sequence for structuring shared understanding of complex, multi-stakeholder problems.
1) Goal — the Future Picture
A shared Future Picture expressed in plain language.
- A statement about what our shared future looks like "once we're there."
- Draft together to get buy-in from each stakeholder, and to build trust that others agree on the same future picture statement.
2) Obstacles — map what’s in the way
Articulate what stands in the way; decompose blockers into tractable sub-parts. Organize the structure (tree or radial).
- At the top level, a handful of major themes that all stakeholders agree are comprehensive.
- Subdivide each major-theme into smaller parts → easier to find potential solutions to smaller parts.
3) Solutions — tied to obstacles
Identify potential solutions for each subdivided obstacle, broadening the option space without prioritizing.
- Invite perspectives from those close to practice and lived experience.
- Avoid prioritization at this stage; selection and testing come later.
4) Resources — making programs visible and mutually legible
Map existing programs and initiatives, while leaving space for new, adapted, and emergent ones that can amplify impact. Present them in ways so that each resource is motivated and enabled to see the wider system and how they and other resources contribute to the shared Goal.
- Visibility helps participants recognize how their efforts relate to one another and to the larger Goal.
- A system-level view fosters awareness, solidarity, and motivation, encouraging voluntary self-alignment rather than centralized coordination.
- Connections among initiatives can spark collaborations and shared momentum, creating outcomes greater than any single effort alone.
- Machine-readable schemas support maps, search, and digital agents, extending this lens across both human and technical ecosystems.
Open datasets
Schema-compliant maps and resource directories.
team.earth/data →Interoperability
ProgramCard & ParticipationTemplate for human-led programs in agent ecosystems.
A2A Human Extension →Open Datasets & Maps
Explore region-specific, schema-compliant datasets and published maps.
MCP Server (Knowledge Graph)
Query GOSR datasets programmatically (no giant JSON in model context).
- MCP server README
- Functions:
query_knowledge_graph,get_resource_details,search_solutions_by_obstacle,get_gosr_hierarchy
Exports & Conversions
From working trees to shareable artifacts for collaborators and funders.
- DOCX outlines (
json2doc.py) - FreeMind mind-maps (
json2mm.py) - Google Maps CSVs (
r2google-maps.py)