AgentStack
Browse Sign in
Browse Why AgentStack Sell Docs
Sign in
SKILL verified MIT Self-run

Gee Agent Skill

skill-fwrog-gee-agent-skill-gee-agent-skill · by Fwrog

Plan, ground, render, validate, preflight, run, and audit reproducible Google Earth Engine Python workflows with source-backed recipes, export monitoring, and run traces. Use for GEE task planning, script generation, dataset or operator retrieval, private-raster handoffs, annual multi-source workflows, knowledge-base distillation, and evidence-bounded evaluation.

No reviews yet
0 installs
10 views
0.0% view→install

Install

$ agentstack add skill-fwrog-gee-agent-skill-gee-agent-skill

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

Verified badge

Passed review? Show it. Paste this badge into your README, it links to the public security report.

AgentStack Verified badge Links to your public security report.
[![AgentStack Verified](https://agentstack.voostack.com/badges/verified.svg)](https://agentstack.voostack.com/security/report/skill-fwrog-gee-agent-skill-gee-agent-skill)

Reliability & compatibility

Security review passed
0 installs to date
no reviews yet
9d ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

Preview Execution monitoring

We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.

How agent discovery & health will work →
Are you the author of Gee Agent Skill? Claim this listing to set pricing, connect Stripe payouts, and keep 70% of every sale.
Sign up to claim

About

GEE Agent Skill

Build reviewable Earth Engine workflows through the gee-skill CLI and the official Earth Engine Python API. Keep the normal path plan-first, source-grounded, traceable, and explicit about what was actually verified.

Core Workflow

  1. Work from the repository root. Check the installed surface with:

gee-skill info --json, gee-skill doctor --json, gee-skill recipe list --json, and gee-skill rules list --json.

  1. Convert the request into an editable plan:

gee-skill plan from-text "" --json. If it returns AMBIGUOUS_TASK, report the missing fields instead of guessing.

  1. Select a registered recipe and retrieve evidence:

gee-skill recipe show --json, gee-skill catalog recommend --task-type --metric --json, and gee-skill search-docs "" --json.

  1. Review the plan and resolve an unclear AOI:

gee-skill plan review --json and gee-skill aoi resolve "" --json.

  1. Render and validate before live work:

gee-skill render --script-out --json and gee-skill validate --json.

  1. Run preflight with an explicit project:

gee-skill preflight --project --json. Treat V03_CONTEXT_REVIEW_REQUIRED as missing reviewed context, not an authentication failure.

  1. Run live only after preflight and explicit confirmation:

gee-skill run --project --confirm-live --json.

  1. Monitor submitted exports:

gee-skill exports list --project --json or gee-skill exports watch --project --task-id --json.

  1. Inspect the persisted trace before reporting results:

gee-skill trace inspect --json.

  1. Run gee-skill eval evals/benchmark_quick_reference.yml --json, then gee-skill eval evals/benchmark_suite.yml --json. Check [docs/capabilitymatrix.md](docs/capabilitymatrix.md) before assigning a readiness label.

Evidence And Claim Boundaries

  • Say live verified only when the capability matrix records a completed public live path. Otherwise use the exact supported level: render/validate verified, dry-run verified, mocked preflight blocked, planned, or experimental.
  • Treat exports and model outputs as workflow artifacts, not scientific conclusions or ground truth.
  • Prefer official Earth Engine documentation and Data Catalog facts. Use papers and community sources only for scoped methods or patterns.
  • When promoting a reusable lesson, add a dataset, rule, failure, or workflow card with a source, last_checked, scope, limitations, and explicit non-claims.
  • Treat omitted private context as intentionally unknown. Do not infer, reconstruct, retrieve, or publish it from nearby files, issue history, or examples.
  • Keep real study identifiers, project and asset IDs, bucket and object names, task IDs, private source files, draft manuscripts, and unpublished results outside the public repository.

Official And User Learning Layers

Keep the versioned repository knowledge base separate from user-owned Obsidian or Markdown learning. A user Skill may retain private evidence and personal rules; it may export only an explicitly approved, sanitized candidate manifest.

Inspect the interface with gee-skill learning contract --json and review a candidate with gee-skill learning review-manifest --json. Treat candidate_review_ready as a transport/privacy result only. Before an item enters this Skill, independently reproduce it, verify official facts, map it to a public target and regression, run the release gates, and obtain maintainer approval in a versioned release. Never read the raw user vault or overwrite the user's local Skill.

Live And Private Data Safety

  • Never request or persist OAuth files, API keys, service-account JSON, tokens, private keys, client secrets, credential paths, or credential contents.
  • Require user authority for billing, organization policy, licenses, interactive authentication, access broadening, destructive asset changes, and unavailable local-to-cloud upload surfaces.
  • For private raster ingestion, request only the minimum non-secret checkpoint needed to resume. Then continue task monitoring, asset-semantic checks, failed-subset retry, preflight, and downstream code without returning routine operations to the user.
  • Never add --force, overwrite, deletion, public access, or broader IAM as a generic recovery step.
  • Keep categorical rasters on reviewed class semantics: no bilinear interpolation of class codes, explicit no-data behavior, reviewed pyramiding, and declared whole-cell versus valid-area fraction denominators.

Read [references/knowledgebase/workflows/private-raster-ingestion-handoff.md](references/knowledgebase/workflows/private-raster-ingestion-handoff.md) for the private-ingestion state machine and [docs/toolpermissions.md](docs/toolpermissions.md) for tool and authority boundaries.

Inputs And Outputs

Prefer editable gee-plan/v0.3 YAML. Record the AOI, dates, dataset IDs, metric, cloud policy, reducer, scale, CRS, export target, validation rules, and claim limitations.

Persist each planned or executed run under outputs/runs//. The run directory should contain the plan, generated script, retrieval and validation evidence, applicable preflight or export-task records, environment metadata, and final report. See [docs/harness.md](docs/harness.md) for the artifact contract.

Read On Demand

  • Setup and command details: [docs/howtostart.md](docs/howtostart.md), [docs/clireference.md](docs/clireference.md), and [docs/troubleshooting.md](docs/troubleshooting.md).
  • Recipes and readiness: [docs/recipes.md](docs/recipes.md), [docs/capabilitymatrix.md](docs/capabilitymatrix.md), [docs/benchmarkprotocol.md](docs/benchmarkprotocol.md), and [docs/benchmarkreference.md](docs/benchmarkreference.md).
  • Evidence and extension: [docs/kgragarchitecture.md](docs/kgragarchitecture.md), [docs/sourcepolicy.md](docs/sourcepolicy.md), [references/knowledgebase/workflows/github-knowledge-distillation.md](references/knowledgebase/workflows/github-knowledge-distillation.md), [references/knowledgebase/workflows/user-local-learning-overlay.md](references/knowledgebase/workflows/user-local-learning-overlay.md), [references/knowledgebase/rules/data-usage-promotion-contract.md](references/knowledgebase/rules/data-usage-promotion-contract.md), and [docs/extending.md](docs/extending.md).
  • Public examples and validation limits: [docs/demogallery.md](docs/demogallery.md) and [docs/remotesensingvalidation.md](docs/remotesensingvalidation.md).

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

No reviews yet, be the first.

Versions

  • v0.1.0 Imported from the upstream source.