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hugging-face

hugging-face is a skill for Claude Code, Codex from CodeInfinity1/Stram. It costs 36 tokens per session (492 once invoked), scanned A, a copy of axolotl, MIT.

A Stram skill for working with Hugging Face, a platform that hosts machine-learning models and datasets. It covers planning, execution, and reproducible model or data workflows.

In plain words
What is it for?
Use it to create model cards, notebooks, benchmark commands, vector-store plans, or scripts for Hugging Face workflows.
Why use it?
It helps organize model and dataset work, including local code execution and checks before using external providers or optional dependencies.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

not rated 11repo 2mo ago A scan 36 tokens copy · 84% MIT

Good fit Use it to create model cards, notebooks, benchmark commands, vector-store plans, or scripts for Hugging Face workflows.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/codeinfinity1/stram/hugging-face
View source ↗ CodeInfinity1/Stram
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.

Any agent
npx skills add CodeInfinity1/Stram --skill hugging-face
Clone the repo
git clone --depth 1 https://github.com/CodeInfinity1/Stram

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 hugging-face

README.md
[![agentmods](https://agentmods.dev/badge/skills/codeinfinity1/stram/hugging-face/github.svg)](https://agentmods.dev/skills/codeinfinity1/stram/hugging-face)
Your own site
<a href="https://agentmods.dev/skills/codeinfinity1/stram/hugging-face"><img src="https://agentmods.dev/badge/skills/codeinfinity1/stram/hugging-face/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for hugging-face

Your own site · 80×15
<a href="https://agentmods.dev/skills/codeinfinity1/stram/hugging-face"><img src="https://agentmods.dev/badge/skills/codeinfinity1/stram/hugging-face.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 36 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 492 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 84% copy Near-identical to another mod 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 5.1 $0.00036 $0.00492
Opus 5.5 $0.00014 $0.00197
Sonnet 5.5 $0.00007 $0.00098
Haiku 4.5 $0.00004 $0.00049

Measured 1mo ago against content hash f5e05371ac88, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

hugging-face 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 1mo ago.

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.

Origin

This is a copy

84% identical to axolotl — 12 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/software-engineering/hugging-face/SKILL.md · 53 lines

How it starts

The opening of the file, as written. The whole thing — 53 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Hugging Face

This is a Stram-native skill. It is authored inside this repository and uses only Stram-owned tools, approval gates, artifacts, and optional dependency records.

When To Use

Use this skill when the user asks for hugging face planning, execution, verification, troubleshooting, or artifact creation inside Stram.

Tool Map

  • tool_search
  • tool_describe
  • capability_surface
  • write_note
  • native_security_policy
  • tool_output_store
  • hugging_face_operation_prepare
  • execute_code
  • python_interpreter
  • process
  • terminal
  • provider_registry
  • mcp_server_catalog
  • mcp_tool_call
  • optional_dependency_installer

Workflow

  1. Clarify the user's concrete hugging face objective, target environment, credentials already configured, and expected artifact or action.
  2. Use tool_search or capability_surface to find the native Stram tools for the domain before choosing a path.
  3. Run safe inspection/readiness steps first and write bounded notes or artifacts under the workspace or data directory.
  4. Create reproducible scripts, notebooks, benchmark commands, model cards, or vector-store plans using bounded local code execution.
  5. Gate GPU/cloud/provider work behind provider_registry, credential readiness, and explicit approval.
  6. Summarize what ran, what was skipped, what remains blocked, and the exact files or records created.

Safety And Boundaries

  • Do not import, execute, or vendor upstream assistant code for this skill.
  • Do not store raw secrets; store only environment variable names, secret references, or readiness booleans.
  • Use approvals for writes, sends, purchases, desktop control, process launches, provider calls, and destructive operations.
  • Do not run network scans, exploit tooling, cloud jobs, or GPU workloads without explicit authorization and scope.

Verification

  • Record concrete evidence paths or tool outputs before claiming completion.
  • Prefer dry-run or prepared artifacts when credentials, hardware, licenses, or live services are missing.
  • If a provider-specific runtime is not configured, report the missing credential or binary by name and stop before live execution.

Read the full file on GitHub · 53 lines

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. 1mo ago First seen · 53 lines · 36 tokens per session scan A f5e05371ac88

Subscribe to this mod's changes

hugging-face is a skill published in the GitHub repository CodeInfinity1/Stram (11 stars, last pushed 2mo ago), licensed MIT. It adds 36 tokens to every session and 492 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 84% identical to axolotl, differing in 12 lines, and is treated as a copy.

Data and AIScientificai-agentai-agentsai-toolsdesktop-automationdesktop-automation-softwaredesktop-automation-windows
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