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 agentmods add skills/boettiger-lab/data-workflows/stac-authoringnpx skills add boettiger-lab/data-workflows --skill stac-authoringgit clone --depth 1 https://github.com/boettiger-lab/data-workflowsWrote 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/boettiger-lab/data-workflows/stac-authoring)<a href="https://agentmods.dev/skills/boettiger-lab/data-workflows/stac-authoring"><img src="https://agentmods.dev/badge/skills/boettiger-lab/data-workflows/stac-authoring.svg" alt="Measured on agentmods" 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 | $0.00082 | $0.09368 |
| Opus 5 | $0.00041 | $0.04684 |
| Sonnet 5 | $0.00016 | $0.01874 |
| Haiku 4.5 | $0.00008 | $0.00937 |
Grade A, and why
stac-authoring scanned grade A with 1 finding 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 today.
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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
1. Check for existing sub-catalog: `curl -s https://s3-west.nrp-nautilus.io/<bucket>/stac-collection.json | jq '.links[] | select(.rel=="child")'` How it starts
The opening of the file, as written. The whole thing — 372 lines — stays where its author put it; the contents beside it link to each section on GitHub.
STAC Authoring
Everything needed for Step 5 (Document) and Step 6 (Register in the parent sub-catalog).
Write STAC and README to /tmp/ and upload with rclone — this repo never contains STAC JSON or README files (AGENTS.md Hard Boundary 1).
⛔ Verify the STAC — don't hand-check the rules
Every STAC rule below is enforced by scripts/verify-stac.py (license, nav links,
asset keys, hex glob, h3:* resolutions, vector:layers, table:columns placement,
per-feature-dup warnings, categorical completeness + PMTiles fields via the two
sibling linters, and a data-backed values == ingested DISTINCT check via the
MCP that automates the #114/#294 lesson). Do not re-verify these by hand or by
spending agent context on MCP SELECT DISTINCT sweeps — run the gate.
# 1. PRE-PUBLISH (static, against the /tmp file you just wrote):
scripts/verify-stac.py --no-data /tmp/stac-collection.json
# Fix every HARD finding before rclone copyto. (Data checks need the data live, so
# they run post-publish; --no-data skips them here.)
# 2. POST-CLUSTER (full, against the live S3 STAC, once data + STAC are published):
scripts/verify-stac.py --bucket <bucket> --dataset <dataset>
# Must exit 0 (no HARD findings). ADVISORY lines are informational.
A *-check-failed finding is HARD, and it means UNVERIFIED — not broken data. If a
data-backed check cannot reach the MCP (a transport failure, a query that will not
complete), the run reports HARD rather than passing quietly: a gate that did not execute
is not a green light. MCPClient.query already retries once, so re-running usually clears
a transient blip. Read it as "check again", not as a defect in the collection — and never
"fix" it by making the check advisory, which is exactly how an unverified collection came
to read as clean (#509).
CI runs the same verifier on the PR (.github/workflows/verify-stac.yml), deriving the
collection(s) from the s3:// paths in the changed catalog/** YAMLs. The gate
evaluates the produced artifact, not the proposal: the cluster run lands after the PR
opens, so a RED check at PR-open (STAC not published yet) is correct — don't merge
before the recipe has actually produced valid output. GitHub status checks don't
auto-refresh from S3, so after your cluster jobs finish, re-fire the check (Actions
→ Verify STAC → Run workflow, or it re-runs on the next push). Merge requires it green.
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.
- today Changed · +1 lines 539ec78e2ba0
- 5d ago First seen · 371 lines · 82 tokens per session scan A 620aa7a8eae8
stac-authoring is a skill published in the GitHub repository boettiger-lab/data-workflows (5 stars, last pushed today), licensed BSD-3-Clause. It adds 82 tokens to every session and 9,368 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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