natural-language-processing-scientist

Think and work like an expert Natural Language Processing Scientist. Use when a task calls for Natural Language Processing Scientist judgment. Reasons from tokenization, data curation (datatrove/NeMo), and evaluation protocols (SacreBLEU/COMET, IFEval, HELM); enforces contamination audits (ConTAM, perplexity separation), paired bootstrap significance, SFT→DPO/RLHF with alignment-tax checks, and ARR/Dodge reproducibility while treating exposure bias, benchmark leakage, prompt-template confounds, and metric gaming as first-class failure modes.

What does this entry provide?

natural-language-processing-scientist is an agent skill entry in ChatHome Skills, sourced from GitHub Skill Search and scored 58/100. # AGENTS.md — Natural Language Processing Scientist Agent You are an experienced natural language processing scientist spanning classical NLP pipelines, pretrai. As an agent skill, it packages a reusable instruction set that AI coding agents such as Codex and Claude Code can load to perform this task without hand-written glue code. ChatHome Skills discovered this entry through its daily ingest of official registries and GitHub discovery queries, and re-verifies repository facts, freshness signals, and install metadata on every run. The quality score weighs official-registry presence, a working install command, license clarity, GitHub star trajectory, and repository freshness — the full formula is on the Sources page. The install command above is ready to copy. Review the last-pushed date and repository status before adding natural-language-processing-scientist to a production agent workflow; the snapshot facts below are point-in-time values from the most recent ingest.

Snapshot facts

Source: GitHub Skill Search
Quality: 58/100
Install method: codex
Repo: K-Dense-AI/scientific-agents
Repo updated: Oct 23, 2026

Install command

codex skill install K-Dense-AI/scientific-agents

Install method: codex

Review the upstream source before running this command.

GitHub project

Quality

Repo stars

Repo updated

Unknown

How is this score calculated?

Weighted across six dimensions, scored 0-100.
Provenance (25): listed in an official or curated registry.
Installability (25): a runnable install command beats a declared transport, which beats a source checkout.
Maintenance (20): recency of the last push; archived entries score zero here.
Adoption (20): repository stars on a log curve.

Security signals

Scan coverage: Install metadata and the indexed document body.

Automated signals from install metadata and a bounded skill body — not a full code security audit and not a recursive source or dependency review.

Discovery note

# AGENTS.md — Natural Language Processing Scientist Agent You are an experienced natural language processing scientist spanning classical NLP pipelines, pretrained language models,

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