glad-personal
Skill4 starsChanged 10 days agoMITView on GitHub
Personal skill manifest and provisioning guide for this user — lists their own skills plus the third-party global skills and plugins they've vetted and want on every machine, with exact install sources, and bundles a copy of their global CLAUDE.md to set up/merge on a new machine too. Use only when explicitly asked to set up skills on a new machine, check what skills are installed vs. missing, or "provision"/"redownload my skills.
We split this skill into the rules it gives an agent
8 rules. About 0 are common, 3 are distinctive, and 5 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈3
Distinctive · estimate
This author's own choices. Worth a look.
5
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 28
Read references/stack.json.
- Very specific: line 30
ownandskillswithtype: "skill": run the entry's install command with -g -y -a claude-code appended. - Very specific: line 34
Set up global
CLAUDE.md: check whether ~/.claude/CLAUDE.md exists. - Very specific: line 36
Exists: read it, then merge in only the sections from the bundled copy that are missing (matched by # heading) — never overwrite.
- Distinctive: line 37
If the bundled file isn't on disk, say so rather than inventing its content.
- Distinctive: line 48
Check the source repo's real account (age, other work, independent references), not just the star count.
- Very specific: line 49
Read the actual SKILL.md (and scripts) before installing.
- Distinctive: line 51
Prefer a Python venv over system-wide installs for any Python dependency.
≈ “Common” is an estimate: at least 1 in 5 of the 308,232 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.
Files
Glad Personal — Skill Manifest
This is not a coding-behavior skill. It's a portable record of which skills this user wants installed — their own, plus third-party skills and plugins referenced from their original sources — so a new machine (or a fresh ~/.claude/skills/) can be brought up to the same state in one pass.
The list lives in references/stack.json (single source of truth): own, skills (third-party; type: "skill" installs with npx skills add, type: "tool" has its own installer), plugins, declined, notProvisioned. A human-readable version is in the repository's catalog/README.md.
Known failure mode: never check skill availability from one source only
Confirmed to actually happen (2026-09-16): an agent ran ls ~/.claude/skills/, concluded no skill fit, and proceeded without one — when a plugin skill (superpowers:writing-plans) matched perfectly. Plugin skills live under ~/.claude/plugins/cache/<marketplace>/<plugin>/ and never appear in ~/.claude/skills/.
The fix: the "available skills" list Claude Code injects into context already merges both sources — trust it. If re-checking manually, always check both:
~/.claude/skills/(npx skills add-installed and tool-installed skills)~/.claude/plugins/installed_plugins.json(Claude Code plugins, e.g.superpowers,vercel)
How to use this on a new machine
- Read
references/stack.json. List what's in~/.claude/skills/and~/.claude/plugins/installed_plugins.json. - Compare. For anything missing:
ownandskillswithtype: "skill": run the entry'sinstallcommand with-g -y -a claude-codeappended. If the repository is cloned,./install.sh --alldoes these in one go — run./install.sh --all --dry-runfirst and show the user.type: "tool"(compiled binary or Python package installers): show the user the command and get an explicit yes before running it — never run these silently.plugins: an agent cannot run/plugin install. Tell the user the exact command to run themselves.
- Skip everything under
declined(rejected on purpose) andnotProvisioned(host-managed, e.g.~/.claude/skills/synced/). - Set up global
CLAUDE.md: check whether~/.claude/CLAUDE.mdexists.- Missing: copy
references/CLAUDE.mdto~/.claude/CLAUDE.md. - Exists: read it, then merge in only the sections from the bundled copy that are missing (matched by
# heading) — never overwrite. Report which sections were added. - If the bundled file isn't on disk, say so rather than inventing its content.
- Missing: copy
- Report what was installed vs. already present vs. skipped vs. needs the user (plugins, tool installers) vs. what was merged into
CLAUDE.md. Don't install or write anything without saying so.
Staleness: references/CLAUDE.md is a point-in-time copy (last synced 2026-10-21). Before relying on it, ask whether the user's live CLAUDE.md has newer content worth re-syncing first.
Plugins differ from skills
Stored in ~/.claude/plugins/cache/…, namespaced (superpowers:systematic-debugging), installed only by the user via /plugin install, and auto-updated (activated on /reload-plugins or the next session). A plugin can change after it was vetted — if its behavior seems off, check whether it updated before assuming the original review was wrong.
How this user likes new skills vetted (apply before adding anything to stack.json)
- Check the source repo's real account (age, other work, independent references), not just the star count.
- Read the actual
SKILL.md(and scripts) before installing. - Flag anything that runs a compiled binary, needs new system dependencies, or can act in the real world (especially browser automation) — confirm before installing.
- Prefer a Python venv over system-wide installs for any Python dependency.
To add a skill: add it to references/stack.json (with vetted, notes, license as the repo declares it), then regenerate the catalog with node scripts/build-catalog.js from the repository root.
In this repository4 other files it gives its agents.
- skills/glad-personal/references/CLAUDE.mdCLAUDE.md
- glad-frontendSkill
- opus-plan-sonnet-buildSkill
- production-readinessSkill
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
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.

