data-download

data-download fetches a selected Cell Painting dataset slice into a local folder.

It is the step that turns a download request into local files that later profiling or segmentation steps can read.

Purpose

Use this skill when you want:

  • local Cell Painting input files on disk

  • a small subset that can be used immediately in the next step

  • a clear record of which files were fetched

Main Outcome

This skill writes the requested Cell Painting files into a local download folder.

In the recorded demo run below, it downloaded the two metadata tables that the later demo steps use:

  • load_data.csv

  • load_data_with_illum.csv

Inputs

This skill reads:

  • a project config such as configs/project_config.demo.json

  • a data request, or a saved plan from data-plan-download

  • an optional output directory

In the demo run below, the request targeted dataset cpg0016-jump, source source_4, and a small metadata subset for BR00117035.

Outputs

  • downloads/load_data.csv The field-level metadata table used by downstream demo steps.

  • downloads/load_data_with_illum.csv The same metadata table with illumination-related path columns.

  • download_plan.json The saved request that was executed for this download.

  • downloads/download_manifest.json The file-level record of what was downloaded.

  • pipeline_skill_manifest.json The run record for this skill invocation.

Agent Demo

This page is based on a real local OpenClaw run against the repository demo config:

  • session id: datadownload-local-v1

  • turn timestamp: 2026-05-05 13:40 UTC

  • model: vibe/gpt-5-mini

Request

I want a tiny local demo subset of the Cell Painting inputs so I can test the next step. Please download the BR00117035 metadata subset from the demo dataset and then tell me what became available locally.

Structured Trace

user_input:
I want a tiny local demo subset of the Cell Painting inputs so I can test the next step. Please download the BR00117035 metadata subset from the demo dataset and then tell me what became available locally.

planner_step_1:
intent:
Load the documented Cell Painting skill routing before choosing a data-access execution skill.
tool_calls:
- read("integrations/openclaw/autodl/workspace/skills/cellpaint-pipeline/SKILL.md")
observed_result:
- the workspace skill file loaded successfully
- the routing guidance identified `data-download` as the public skill for fetching local input files

planner_step_2:
intent:
Confirm the current skill catalog and inspect the documented description for the selected skill.
tool_calls:
- exec("cd /root/pipeline/CellPainting-Claw && /root/autodl-tmp/miniconda3_envs/lyx_env/bin/cellpainting-skills list && echo '---DESCRIBE---' && /root/autodl-tmp/miniconda3_envs/lyx_env/bin/cellpainting-skills describe --skill data-download")
observed_result:
- the public skill catalog listed `data-download`
- the skill description confirmed that this step downloads one configured dataset slice into a local cache directory

planner_step_3:
intent:
Locate the documented demo subset and run the actual metadata download into the named demo output directory.
tool_calls:
- exec("cd /root/pipeline/CellPainting-Claw && /root/autodl-tmp/miniconda3_envs/lyx_env/bin/cellpainting-skills run --config /root/pipeline/CellPainting-Claw/configs/project_config.demo.json --skill data-download --dataset-id cpg0016-jump --source-id source_4 --subprefix workspace/load_data_csv/2021_04_26_Batch1/BR00117035 --output-dir /root/pipeline/CellPainting-Claw/demo/workspace/outputs/agent_demo_data_download")
- process.poll("nova-crest")
observed_result:
- skill_key = data-download
- resolved prefix = cpg0016-jump/source_4/workspace/load_data_csv/2021_04_26_Batch1/BR00117035/
- matched files = 2
- downloaded files = 2
- the download completed successfully

planner_step_4:
intent:
Inspect the written output tree and report exactly which files were fetched.
tool_calls:
- exec("cd /root/pipeline/CellPainting-Claw && find demo/workspace/outputs/agent_demo_data_download -maxdepth 3 -type f | sort")
observed_result:
- download_plan.json
- downloads/download_manifest.json
- downloads/load_data.csv
- downloads/load_data_with_illum.csv
- pipeline_skill_manifest.json

final_answer_snapshot:
The demo metadata subset downloaded successfully and made two local metadata tables available for the next step.

Observed Result

The recorded run downloaded one small Cell Painting metadata subset from:

  • dataset cpg0016-jump

  • source source_4

  • gallery prefix cpg0016-jump/source_4/workspace/load_data_csv/2021_04_26_Batch1/BR00117035/

The saved run record showed:

  • matched files: 2

  • downloaded files: 2

The fetched files were:

  • load_data.csv

  • load_data_with_illum.csv

Recorded Reply

I downloaded the requested demo metadata subset successfully.

Source used:
- dataset: `cpg0016-jump`
- source: `source_4`
- gallery prefix: `cpg0016-jump/source_4/workspace/load_data_csv/2021_04_26_Batch1/BR00117035/`

What is now available locally:
- `load_data.csv`
- `load_data_with_illum.csv`

Summary:
- matched files: `2`
- downloaded files: `2`

This was a metadata-only download. In practical terms, you now have the field-level image metadata needed to start the next profiling or segmentation step.

Next Skills