Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Lzy599775/agent-auto-sci-skills --skill kdense-geospatial-rs-selectedgit clone --depth 1 https://github.com/Lzy599775/agent-auto-sci-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/lzy599775/agent-auto-sci-skills/kdense-geospatial-rs-selected)<a href="https://agentmods.dev/skills/lzy599775/agent-auto-sci-skills/kdense-geospatial-rs-selected"><img src="https://agentmods.dev/badge/skills/lzy599775/agent-auto-sci-skills/kdense-geospatial-rs-selected/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/lzy599775/agent-auto-sci-skills/kdense-geospatial-rs-selected"><img src="https://agentmods.dev/badge/skills/lzy599775/agent-auto-sci-skills/kdense-geospatial-rs-selected.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00096 | $0.00389 |
| Opus 5 | $0.00048 | $0.00195 |
| Sonnet 5 | $0.00019 | $0.00078 |
| Haiku 4.5 | $0.00010 | $0.00039 |
Grade A, and why
kdense-geospatial-rs-selected scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
K-Dense Geospatial / Remote Sensing Selected
This wrapper packages selected Geospatial Science & Remote Sensing skills from K-Dense-AI/scientific-agent-skills.
Use it when a task needs library-level or workflow-level support for:
geomastergeopandas- vector and raster handling;
- CRS and geometry operations;
- remote-sensing feature workflows;
- spatial analysis and spatial ML implementation details.
Local Adaptation
Use these upstream skills with local geospatial rules:
- Check CRS, units, topology, geometry validity, and spatial resolution before analysis.
- Keep exposure, accessibility, availability, quality, and use conceptually separate.
- Record buffer/network/travel-time assumptions in methods-ready language.
- For environmental exposure, state temporal window, season, data product, and aggregation rule.
- For maps, check legends, classification, scale, north arrow needs, and projection disclosure.
For domain-specific guidance, also read:
../agent-auto-sci-geospatial/references/k_dense_geospatial_rs_mapping.md../agent-auto-sci-geospatial/references/exposure_accessibility_definitions.md
Must Not Do
- Do not convert spatial units silently.
- Do not use Euclidean buffers when network access is required without explaining the limitation.
- Do not treat remote-sensing classification output as ground truth without validation.
What ships with it
33 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- agents/openai.yaml 371 B
- LICENSE.upstream.md 1.0 KB
- NOTICE.md 538 B
- subskills/k-dense/geomaster/README.md 3.1 KB
- subskills/k-dense/geomaster/references/advanced-gis.md 10 KB
- subskills/k-dense/geomaster/references/big-data.md 8.3 KB
- subskills/k-dense/geomaster/references/code-examples.md 12 KB
- subskills/k-dense/geomaster/references/coordinate-systems.md 8.7 KB
- subskills/k-dense/geomaster/references/core-libraries.md 6.4 KB
- subskills/k-dense/geomaster/references/data-sources.md 8.8 KB
- subskills/k-dense/geomaster/references/gis-software.md 8.7 KB
- subskills/k-dense/geomaster/references/industry-applications.md 13 KB
- subskills/k-dense/geomaster/references/machine-learning.md 12 KB
- subskills/k-dense/geomaster/references/programming-languages.md 11 KB
- subskills/k-dense/geomaster/references/remote-sensing.md 9.9 KB
- subskills/k-dense/geomaster/references/scientific-domains.md 10 KB
- subskills/k-dense/geomaster/references/specialized-topics.md 10 KB
- subskills/k-dense/geomaster/references/troubleshooting.md 11 KB
- subskills/k-dense/geomaster/SKILL.md 12 KB
- subskills/k-dense/geopandas/references/crs-management.md 8.7 KB
- subskills/k-dense/geopandas/references/data-io.md 12 KB
- subskills/k-dense/geopandas/references/data-structures.md 7.4 KB
- subskills/k-dense/geopandas/references/geometric-operations.md 9.5 KB
- subskills/k-dense/geopandas/references/spatial-analysis.md 9.6 KB
- subskills/k-dense/geopandas/references/visualization.md 8.5 KB
- subskills/k-dense/geopandas/scripts/_common.py 21 KB runs code
- subskills/k-dense/geopandas/scripts/crs_reprojection_plan.py 7.2 KB runs code
- subskills/k-dense/geopandas/scripts/export_plan.py 11 KB runs code
- subskills/k-dense/geopandas/scripts/geometry_validity_report.py 7.3 KB runs code
- subskills/k-dense/geopandas/scripts/sensitive_coordinates_checklist.py 8.8 KB runs code
- subskills/k-dense/geopandas/scripts/spatial_join_audit.py 13 KB runs code
- subskills/k-dense/geopandas/scripts/vector_inventory.py 4.4 KB runs code
- subskills/k-dense/geopandas/SKILL.md 13 KB
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 39 lines · 96 tokens per session scan A 5338bcf80d6b
kdense-geospatial-rs-selected is a skill published in the GitHub repository Lzy599775/agent-auto-sci-skills (2 stars, last pushed 5d ago), licensed MIT. It adds 96 tokens to every session and 389 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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