data-workflows: Instructions file for Codex

AGENTS.md

data-workflows AGENTS.md is an instructions file for Codex, OpenCode from boettiger-lab/data-workflows. It costs 12,256 tokens per session, scanned C, original, BSD-3-Clause.

Agent instructions for a geospatial data pipeline that converts datasets into cloud-native formats on Kubernetes, a system for running containerized jobs. They define required boundaries, workflow rules, and when to load specialized skills.

In plain words
What is it for?
Use them when ingesting, re-hexing, tuning, troubleshooting, or documenting geospatial datasets.
Why use it?
They help agents choose the right procedure, preserve the canonical storage and publishing workflow, and avoid unsafe processing decisions.

Instructions file for CodexOpenCode

Written for Codex and OpenCode: the file is AGENTS.md. Also seen: reads .claude/ paths; mentions Claude Code; mentions AGENTS.md.

This is boettiger-lab/data-workflows's own configuration. It tells Codex and OpenCode how to work on data-workflows itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything data-workflows configures →

Reuse

Borrowing it

Nothing to install: this file belongs to boettiger-lab/data-workflows. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/boettiger-lab/data-workflows/main/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/boettiger-lab/data-workflows

Made for: Codex, OpenCode.

Wrote this? Show the measurements

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README.md
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Per session 12,256 This file is loaded in full into every session.
When invoked 12,256 The same file — it is already loaded in full.
Security scan C 2 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.12256 $0.12256
Opus 5.5 $0.04902 $0.04902
Sonnet 5.5 $0.02451 $0.02451
Haiku 4.5 $0.01226 $0.01226

Measured 3d ago against content hash a49bd1133eb4, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade C, and why

data-workflows AGENTS.md scanned grade C with 2 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 3d 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.

Downloads and executes remote codehighSupply chain

curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.

curl -s https://data-requests.nrp-nautilus.io/api/requests | python3 -m json.tool

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

- Read: `curl https://s3-west.nrp-nautilus.io/<bucket>/stac-collection.json`
AGENTS.md · 678 lines

How it starts

The opening of the file, as written. The whole thing — 678 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Agent Instructions: Dataset Processing

You work in data-workflows, which uses cng-datasets to convert geospatial data into cloud-native formats on Kubernetes. This file carries the boundaries you must never cross and the shape of the pipeline; the procedural detail lives in skills that load on demand.

Skills — load the one that matches what you are doing

These are .claude/skills/<name>/SKILL.md in this repo. They work in Claude Code and opencode alike (both read .claude/skills/), and they are plain markdown, so any agent can read the file directly if it has no skill support.

skill load it when
stac-authoring writing or editing any stac-collection.json or dataset README (Steps 5–6)
raster-hexing ingesting or re-hexing a GeoTIFF/COG — resolution, reducer, mosaicking
hex-tuning a hex job OOMs, or choosing native/parent H3 resolutions and chunk sizes
job-troubleshooting a job fails, hangs, or a published parquet will not read
dataset-recipes starting an ingest that resembles a worked example
armada-pipeline armadactl will not authenticate, a k8s job hits the 200-completion cap, or you are choosing between the k8s and Armada pathways
pod-preemption indexed-job pods die and retry for no apparent reason, you are working out which indexes actually need re-running, you are choosing a priority class or sizing requests (NRP usage policy), or before submitting any job whose pods run over an hour

Everything below is always in force, skill or no skill.

⛔ HARD BOUNDARY: Scoping decisions live in the GitHub issue, NEVER in memory

Every decision that defines what a dataset task delivers — spatial extent (full upstream coverage vs. a regional clip), H3 resolution, reducer, source product/version, target bucket and naming — MUST be written into the GitHub issue before you act on it. Sessions are disposable: the laptop dies, agent memory is wiped, a different agent picks up the task. The issue is the single source of truth that survives all of that. Treat yourself like any professional developer — nobody is expected to carry scope "in their head," and you must not rely on agent memory (~/.claude/.../memory) for scope. Memory is for how you work, never what a task delivers.

Read the full file on GitHub · 678 lines

Changes

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.

  1. 3d ago Changed a49bd1133eb4
  2. 8d ago Changed · +2 lines · +377 tokens per session b97c91d128aa
  3. 10d ago Changed · +7 lines · +253 tokens per session 6deedf6971d2
  4. 23d ago Changed · +9 lines · +280 tokens per session 0e5a412c818f
  5. 27d ago Changed · +104 lines · +1,693 tokens per session 113955f2d07a
  6. 1mo ago Changed · +11 lines · +159 tokens per session ec1b7eb9f09d
  7. 1mo ago Changed · -31 tokens per session b5c8688ea4ce
  8. 1mo ago Changed · +2 lines · +344 tokens per session 17212d444677
  9. 1mo ago Changed · +27 lines · +425 tokens per session a6fc8edea3be
  10. 2mo ago First seen · 516 lines · 8,756 tokens per session scan C ae6f1112deea

Subscribe to this mod's changes

data-workflows AGENTS.md is an instructions file published in the GitHub repository boettiger-lab/data-workflows (5 stars, last pushed 2d ago), licensed BSD-3-Clause. It adds 12,256 tokens to every session, about $0.0490 per session on Opus 5.5. A static security scan graded it C with 2 findings (downloads and executes remote code, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

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data-workflows AGENTS.md next to 6 instructions from other repositories
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deepseek-harness AGENTS.mddeepseek-ai/deepseek-harnessInstructions file274k2d agoMITA4,313Codex, OpenCode