Data And Feature Columns

What it does

When your agent uses it

• Tasks that involve Embeddings

Example prompts

• “/data-and-feature-columns”

Requirements

• Python 3

Workflow steps

8 steps, taken from the first numbered list in SKILL.md.

1. 1List every raw feature and classify it as one categorical id, a dense scalar/vector, or a variable-length list of categorical ids.
2. 2Encode one-id categorical fields as integers and use SparseFeat, or set use_hash=True with dtype="string" when hashing string values on…
3. 3Use DenseFeat(name, dimension) for dense vectors; make each input array shape match the declared dimension.
4. 4Use VarLenSparseFeat(SparseFeat(...), maxlen=...) for multi-value or sequence ids. Pad every row to (batch_size, maxlen).
5. 5Keep 0 reserved for padding when a sequence field relies on masking instead of an explicit length_name.
6. 6Use the same embedding_name only when fields truly share one embedding table and have the same vocabulary size, embedding dimension, and…
7. 7Call get_feature_names(linear_feature_columns + dnn_feature_columns) and build model_input = {name: array for name in feature_names}.
8. 8Route to

What it can do on your machine

Read from SKILL.md and the folder at commit ac3fe1a. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  Ships 1 file in scripts/ (Python), which the agent can run.

  Shell commands in SKILL.md call:

  • python

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  No URLs in SKILL.md.

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names no API keys, tokens, secrets or passwords.

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Data And Feature Columns loads about 1.1k tokens when it runs, and up to ~7.5k if it reads all its reference files. Until then it costs about 49 tokens; SKILL.md has 440 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~49

When it runs · the whole SKILL.md, loaded when a task matches

~1.1k

With references · SKILL.md plus every file in references/, read only if the agent opens them

~7.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from VectorSpaceLab/AREX-Skill at commit ac3fe1a, republished under its Apache-2.0 licence (© VectorSpaceLab). 440 words, ~1,128 tokens.

name

data-and-feature-columns

description

Use this DeepCTR sub-skill for SparseFeat, DenseFeat, VarLenSparseFeat, hashing, embedding sharing, input dictionaries, and tabular or sequence feature-column validation.

disable-model-invocation

true

metadata.disco-role

operating

license

Apache 2.0

{
  "features": [
    {"type": "SparseFeat", "name": "item_id", "vocabulary_size": 1001, "embedding_dim": 8},
    {"type": "DenseFeat", "name": "score", "dimension": 1},
    {
      "type": "VarLenSparseFeat",
      "name": "hist_item_id",
      "maxlen": 4,
      "length_name": "seq_length",
      "sparsefeat": {"name": "hist_item_id", "vocabulary_size": 1001, "embedding_dim": 8, "embedding_name": "item_id"}
    }
  ]
}

python sub-skills/data-and-feature-columns/scripts/validate_feature_spec.py feature_spec.json

© VectorSpaceLab, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files (scripts, references) in skills/repositories/repo-skills/deepctr/sub-skills/data-and-feature-columns of VectorSpaceLab/AREX-Skill.

• SKILL.md
• references/data-formats.md
• references/feature-columns.md
• references/troubleshooting.md
• scripts/validate_feature_spec.py

Open the folder on GitHubat commit ac3fe1a