numcodecs-compression-decompression-starter

numcodecs-compression-decompression-starter is a skill for Claude Code, Codex from ma-compbio-lab/SkillFoundry. It costs 0 tokens per session (266 once invoked), scanned A, original, Apache-2.0.

A starter workflow that compresses and decompresses a small integer matrix with numcodecs, a Python library for encoding data.

In plain words
What is it for?
Testing a fixed compression setup, checking recovered matrix data, and creating a small regression fixture.
Why use it?
It checks that the data survives a lossless round trip and records basic details about the encoded result.

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/ma-compbio-lab/skillfoundry/numcodecs-compression-decompression-starter
Any agent
npx skills add ma-compbio-lab/SkillFoundry --skill numcodecs-compression-decompression-starter
Clone the repo
git clone --depth 1 https://github.com/ma-compbio-lab/SkillFoundry

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for numcodecs-compression-decompression-starter

README.md
[![agentmods](https://agentmods.dev/badge/skills/ma-compbio-lab/skillfoundry/numcodecs-compression-decompression-starter.svg)](https://agentmods.dev/skills/ma-compbio-lab/skillfoundry/numcodecs-compression-decompression-starter)
Your own site
<a href="https://agentmods.dev/skills/ma-compbio-lab/skillfoundry/numcodecs-compression-decompression-starter"><img src="https://agentmods.dev/badge/skills/ma-compbio-lab/skillfoundry/numcodecs-compression-decompression-starter.svg" alt="Measured on agentmods" height="20"></a>
Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 266 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00000 $0.00266
Opus 5 $0.00000 $0.00133
Sonnet 5 $0.00000 $0.00053
Haiku 4.5 $0.00000 $0.00027

Measured 4d ago against content hash 46e43f3addc4, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

numcodecs-compression-decompression-starter 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 4d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/run_numcodecs_compression_decompression.py, tests/test_run_numcodecs_compression_decompression.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/data-acquisition-and-dataset-handling/numcodecs-compression-decompression-starter/SKILL.md · 28 lines

What it actually says

numcodecs Compression / Decompression Starter

Use this skill to round-trip a small integer matrix through a deterministic numcodecs compressor and inspect the encoded payload summary.

What This Skill Does

  • reads a tiny tabular integer matrix
  • encodes the matrix bytes with numcodecs.Blosc
  • decodes the payload and verifies lossless recovery
  • reports shape, dtype, encoded byte count, and simple row statistics

When To Use It

  • when you need a starter for compression-decompression
  • when you want a repo-local numcodecs example outside the full Zarr stack
  • when you need a small regression fixture for round-trip codec checks

Run

./slurm/envs/data-tools/bin/python skills/data-acquisition-and-dataset-handling/numcodecs-compression-decompression-starter/scripts/run_numcodecs_compression_decompression.py --input skills/data-acquisition-and-dataset-handling/numcodecs-compression-decompression-starter/examples/toy_matrix.tsv --out scratch/numcodecs/toy_matrix_summary.json

Notes

  • The codec configuration is fixed so the canonical asset stays stable.
  • The example is intentionally tiny and integer-only; validate codec choices on real payloads before production use.
Files

What ships with it

6 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.

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. 4d ago First seen · 28 lines · 0 tokens per session scan A 46e43f3addc4

Subscribe to this mod's changes

numcodecs-compression-decompression-starter is a skill published in the GitHub repository ma-compbio-lab/SkillFoundry (38 stars, last pushed 4mo ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 266 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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