Scan Arm Learning Paths and install guides for stale-content risk.

Custom licenceAuto-check passedEducation

Install Stale Content Review

skills CLI
$ npx skills add ArmDeveloperEcosystem/arm-learning-paths --skill stale-content-review -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install ArmDeveloperEcosystem/arm-learning-paths stale-content-review --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/ArmDeveloperEcosystem/arm-learning-paths.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.github/skills/stale-content-review .claude/skills/stale-content-review && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
stale-content-review
GitHub stars
154
Token cost
~991 tokens
SKILL.md length
424 words
Files
3 (incl. scripts, references)
Skills in repo
15
Repo updated
First seen
Licence
Custom licence

At a glance

Scan Arm Learning Paths and install guides for stale-content risk.

  • Works in 4 steps: Identify the review scope. For periodic… → Run scripts/stale_content_scan.py for a… → Review the highest-scoring files and… → …
  • The user asks to periodically flag content that may need maintenance
  • SKILL.md covers Prerequisites, Workflow, Validation rules and Script usage, plus 2 more sections
  • Runs Python scripts from its folder; calls python3

What it does

Stale Content Review is an agent skill from ArmDeveloperEcosystem/arm-learning-paths. Scan Arm Learning Paths and install guides for stale-content risk. Use when the user asks to periodically flag content that may need maintenance, freshness review, dependency drift review, screenshot or UI review, latest or unpinned version review, or a report of likely stale pages.

Its SKILL.md is about 990 tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including scripts and reference files (for example `references/staleness-signals.md` and `scripts/stale_content_scan.py`).

It sits in Education, covering Curriculum and course design. The repository describes itself as: Arm Learning Paths: a repository of how-to content for software developers.

When your agent uses it

  • The user asks to periodically flag content that may need maintenance
  • Freshness review
  • Dependency drift review
  • Unpinned version review

Example prompts

  • “/stale-content-review”

Requirements

  • Python 3

Workflow steps

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

  1. Identify the review scope. For periodic scans, default to content/learning-paths and content/install-guides.
  2. Run scripts/stale_content_scan.py for a deterministic first pass.
  3. Review the highest-scoring files and sample lines before drawing conclusions.
  4. Summarize what each selected guide or page does, the dependencies or moving parts it relies on, and the review flags a human should…

What it can do on your machine

Read from SKILL.md and the folder at commit 44a1644. 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:

    • python3

    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

Stale Content Review loads about 991 tokens when it runs, and up to ~1.8k if it reads all its reference files. Until then it costs about 76 tokens; SKILL.md has 424 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~76
When it runs · the whole SKILL.md, loaded when a task matches
~991
With references · SKILL.md plus every file in references/, read only if the agent opens them
~1.8k

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

Auto-check passed

The automated check found no risky patterns in SKILL.md.

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

Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 424 words (~991 tokens).

“Use this skill to find Learning Paths and install guides that might need human maintenance review. This skill is report-only by default: flag risk, provide evidence, and leave fixes to the relevant owner unless the user explicitly asks for edits.”

— opening of SKILL.md by ArmDeveloperEcosystem, Custom licence
name
stale-content-review

Read the full SKILL.md on GitHub

Files

SKILL.md and 2 other files (scripts, references) in .github/skills/stale-content-review of ArmDeveloperEcosystem/arm-learning-paths.

  • SKILL.md
  • references/staleness-signals.md
  • scripts/stale_content_scan.py

Open the folder on GitHubat commit 44a1644

Compare with similar skills

Stale Content Review next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Stale Content Review compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Stale Content Review this skillArmDeveloperEcosystem/arm-learning-paths154—~991Automated safety check: PassCustom licence
AI Engineering Placement Quizrohitg00/ai-engineering-from-scratch66k—~2kAutomated safety check: PassMIT
K-12 Core Literacy Lesson DesignTHU-MAIC/OpenMAIC40k—~2.4kAutomated safety check: PassMIT
AnythingAtlasLiuziyu77/AnythingAtlas195—~3.6kAutomated safety check: PassApache-2.0
Codex Skill Self-AssessmentFlorianBruniaux/claude-code-ultimate-guide6.1k—~2.3kAutomated safety check: PassCC-BY-SA-4.0
Curriculum PlannerTHU-MAIC/OpenMAIC40k—~2.8kAutomated safety check: PassMIT

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Categories

Questions about Stale Content Review

What does Stale Content Review do?

Scan Arm Learning Paths and install guides for stale-content risk. Stale Content Review is an agent skill from ArmDeveloperEcosystem/arm-learning-paths. Scan Arm Learning Paths and install guides for stale-content risk.

When should I use Stale Content Review?

Stale Content Review fits situations like: the user asks to periodically flag content that may need maintenance; freshness review; dependency drift review; unpinned version review.

How do I install Stale Content Review in Claude Code?

Run `npx skills add ArmDeveloperEcosystem/arm-learning-paths --skill stale-content-review -a claude-code`. Or copy the skill folder (.github/skills/stale-content-review in ArmDeveloperEcosystem/arm-learning-paths) into .claude/skills/stale-content-review in your project. Claude Code loads it when a task matches its description.

How do I install Stale Content Review in Codex?

Run `npx skills add ArmDeveloperEcosystem/arm-learning-paths --skill stale-content-review -a codex`. Or copy the skill folder (.github/skills/stale-content-review in ArmDeveloperEcosystem/arm-learning-paths) into .agents/skills/stale-content-review in your project. Codex loads it when a task matches its description.

Can I use Stale Content Review in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ArmDeveloperEcosystem/arm-learning-paths --skill stale-content-review -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/stale-content-review, .gemini/skills/stale-content-review, .github/skills/stale-content-review and .opencode/skills/stale-content-review in your project.

What does Stale Content Review need to run?

Going by SKILL.md and its folder, Stale Content Review needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3.

Does Stale Content Review access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Stale Content Review safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Stale Content Review use?

Stale Content Review has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.

How many tokens does Stale Content Review use?

About 991 tokens (SKILL.md is roughly 4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 807 tokens, read only when the agent opens those files.

What are the alternatives to Stale Content Review?

Skills that share tags, products or a category with Stale Content Review: AI Engineering Placement Quiz (rohitg00/ai-engineering-from-scratch, 66k stars), K-12 Core Literacy Lesson Design (THU-MAIC/OpenMAIC, 40k stars), AnythingAtlas (Liuziyu77/AnythingAtlas, 195 stars) and Codex Skill Self-Assessment (FlorianBruniaux/claude-code-ultimate-guide, 6.1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Stale Content Review?

ArmDeveloperEcosystem (a GitHub organization) maintains it in ArmDeveloperEcosystem/arm-learning-paths, which has 154 GitHub stars. The repository holds 15 skills in this directory. The repository was last updated on October 7, 2026.

Source: ArmDeveloperEcosystem/arm-learning-paths on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.