agentleFS
glrodaszglrodasz/dotfiles/skills/shell-aliases-social/SKILL.md

shell-aliases-social

Skill20 starsChanged 15 days agoMITView on GitHub

Regenerate a shareable shell-aliases JSON from the user's shell config — curated, universally-useful aliases and functions with usage frequency from shell history. Use when the user runs /shell-aliases-social, optionally with paths that override the defaults — to refresh, update, regenerate, share, or export their shell aliases as the shell aliases social media JSON (aliases JSON), a shareable list of their zsh aliases and functions.

The file

We split this skill into the rules it gives an agent

2 rules. About 0 are common, 2 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Read the user's shell config and history, curate the most interesting and universally-useful aliases and functions, and write them to a …

    line 15
  2. Distinctive:

    No sensitive information leaked into the file — the output is typically committed to a public repo.

    line 80

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Shell Aliases Social JSON

Read the user's shell config and history, curate the most interesting and universally-useful aliases and functions, and write them to a shareable JSON file. Nothing private (internal hosts, project IDs, credentials) reaches the file — it is committed to a public repo.

Inputs

Defaults; each is overridable by invocation args.

  • Shell config: ~/.zshrc (or the actual config, e.g. ~/dotfiles/zsh/.zshrc if symlinked), plus ~/.zshrc.local if present
  • History: ~/.zsh_history — rank the top 100 most-used commands for frequency. This strips zsh's extended-history prefix (: <time>:<duration>;):

    LC_ALL=C sed -E 's/^: [0-9]+:[0-9]+;//' ~/.zsh_history | awk '{print $1}' \
      | sort | uniq -c | sort -rn | head -100
  • Output: <dotfiles repo>/zsh/shell-aliases-social.json; if no dotfiles repo, ask where to write
  • Author: git config user.name (or GitHub handle) — never hardcode

Phase 1 — Curate entries

Include an alias/function if it meets at least one criterion:

  • Used frequently (appears often in shell history)
  • Universally useful (any developer could benefit, not project-specific)
  • Creative or fun (worth sharing for inspiration)

Always skip:

  • Anything referencing private/internal domains, project IDs, service accounts, hostnames, or credentials
  • Simple one-word wrappers with no added value
  • Internal helper functions prefixed with _

Phase 2 — Write the JSON

{
  "meta": {
    "author": "<from git config>",
    "source": "~/.zshrc",
    "generated": "YYYY-MM-DD"
  },
  "entries": [
    {
      "name": "string",
      "type": "alias | function",
      "category": "git | dev | cleanup | utility | fun",
      "command": "string (actual shell definition, abbreviated if long)",
      "description": "short human-readable tagline",
      "usage_frequency": "high | medium | low"
    }
  ]
}
  • usage_frequency comes from the history ranking: high = top 10, medium = ranks 11–50, low = ranks 51–100 or not ranked but kept for being useful or fun.
  • Sort entries by category in the order above (git, dev, cleanup, utility, fun), then by name, so regenerating gives a stable diff.

Phase 3 — Verify

  1. Valid JSON: python3 -m json.tool <output> >/dev/null.
  2. No sensitive information leaked into the file — the output is typically committed to a public repo. Remove any leaked entry and re-check until both pass.

Report

Compare against the committed version (git -C <dotfiles repo> diff HEAD -- <output>) and print:

## Shell aliases social — <date>

### Added
- <entry name — why it qualified>

### Removed
- <entry name — why it was dropped>

### Updated
- <entry name — what changed: command, description, or frequency>

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.