kdense-transformers

Hugging Face Transformers for loading Hub models, running pipeline inference, text generation, and Trainer fine-tuning on NLP, vision, audio, and multimodal tasks. Use when working with AutoModel, pipelines, tokenizers, or TrainingArguments—not for general ML outside the Transformers library.

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Repository: eightmm/codex-science
Last source activity: July 10, 2026 at 05:18
Detected SKILL.md language: English
Stars: 2
Forks: 0

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Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.

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npx skills add https://github.com/eightmm/codex-science --skill kdense-transformers

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Review the source files

Read SKILL.md and any companion files shown by SkillsMP before deciding whether to install.

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2 files

SKILL.md

Source instructions · Read-only preview

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quantitative-research

Execute auditable quantitative research across preregistered study design, statistical inference, numerical verification, dimensional analysis, uncertainty propagation, counterexample search, and formal proof. Use when a scientific or mathematical question needs actual computation and machine-readable evidence rather than only explanation.

2026-08-04

statistical-decision-analysis

Compare finite actions under uncertainty with explicit states, loss, utility or risk-neutral payoff, priors, experiment likelihoods, and a declared decision criterion. Use for Bayes risk, expected utility or payoff, pure-action minimax, minimax regret, dominance, posterior decision policies, EVPI/EVSI, experiment-cost decisions, and prior-threshold sensitivity; do not use for ordinary statistical testing, causal identification, strategic games, or MDP/POMDP/RL planning.

2026-08-04

cx-statistical-decision-analysis

2026-08-04

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Kdense Transformers

Use this Codex adapter for the pinned upstream scientific skill.

Catalog status

Status: inactive

Source: kdense

Audit reasons: credentials-required, unsafe-instruction

Upstream license: Apache-2.0 license

Inventory: ../../inventory.json

Upstream instructions: ../../../vendor/scientific-agent-skills/skills/transformers/SKILL.md

Procedure

Resolve the plugin root as three directories above this skill directory.

Read the matching inventory record and verify its status, reasons, source path, and pinned revision.

Do not read the upstream instructions until the user has seen every audit reason and given explicit acknowledgement. Acknowledgement permits instruction inspection only.

Treat upstream frontmatter as source metadata, not as Codex configuration. Follow the instruction body only where it is compatible with available Codex tools and the current user-approved plan.

Treat tools named for another agent runtime as capability requests. Map them to an available Codex tool only when the behavior is equivalent; otherwise report the unavailable capability.

Ask before credentials, package installation, new network hosts, remote compute, writes, paid services, destructive actions, or imported executable code.

Use $science-provenance for produced scientific outputs and $science-review before presenting scientific claims.

Boundaries

This wrapper does not grant credentials, network access, package installation, or script execution.

Do not change an inactive record to active from inside a research task.

Preserve failures, uncertainty, source identifiers, and licensing constraints.

name	kdense-transformers
description	Hugging Face Transformers for loading Hub models, running pipeline inference, text generation, and Trainer fine-tuning on NLP, vision, audio, and multimodal tasks. Use when working with AutoModel, pipelines, tokenizers, or TrainingArguments—not for general ML outside the Transformers library.