data-provenance

A guide for recording the full history of work performed on ENCODE data, including tool versions, reference files, scripts, settings, and times.

In plain words
What is it for?
Use it when downloading, filtering, merging, lifting over, or processing ENCODE files and when running bioinformatics pipelines.
Why use it?
It makes analyses reproducible and provides the details needed to write accurate methods sections for research papers.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/ammawla/encode-toolkit/data-provenance
Any agent
npx skills add ammawla/encode-toolkit --skill data-provenance
Clone the repo
git clone --depth 1 https://github.com/ammawla/encode-toolkit

Made for: Claude Code, Codex.

Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 6,487 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown 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 $0.00000 $0.06487
Opus 5 $0.00000 $0.03243
Sonnet 5 $0.00000 $0.01297
Haiku 4.5 $0.00000 $0.00649

Measured 2d ago against content hash 440cf2038aaf, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

data-provenance 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 2d 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.

plugin/skills/data-provenance/SKILL.md · 647 lines

The source is not reproduced here

Licensed AGPL-3.0

The repository is licensed AGPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.

Read it on GitHub

Files

What ships with it

1 file 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.

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. 2d ago First seen · 647 lines · 0 tokens per session scan A 440cf2038aaf

Subscribe to this mod's changes

data-provenance is a skill published in the GitHub repository ammawla/encode-toolkit (24 stars, last pushed 1mo ago), licensed AGPL-3.0. It costs nothing until one of its globs matches a file; then it loads 6,487 tokens. 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 2026-08-30.

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