Save Loaded Skills as a New Plugin

Package the skills loaded in THIS conversation as a fresh .plugin file — either the iterated versions (if you modified them), or the originals (if you loaded but never clicked Save plugin). The saved plugin reflects the current in-context state.

This saves what /skills-load brought in. To fetch skills from GitHub, use /skills-load. To refresh installed plugins from their GitHub sources, use /skills-update. To package already-installed skills for sharing, use /skills-share.

When to use this

• You ran /skills-load <github-url> and iterated one or more skills — save the iterated versions
• You ran /skills-load <github-url> but never clicked Save plugin — save it now so you can install with one click
• You want a named snapshot of the current in-context skill state

How it works

Skills loaded via /skills-load are injected into the conversation as ### LOADED SKILL: {name} blocks. This skill gathers skills from two sources unconditionally — (A) conversation markers, which preserve any iterations, and (B) already-installed skills-toolkit plugins on disk — then cross-references them to pick the right action: save iterations, install a load that was never saved, save originals post-compaction, or report nothing to do. The result is packaged as a .plugin file presented for install via Cowork's "Save plugin" button.

Step 1: Discover loaded skills (two sources)

Skills can come from two sources. Gather from BOTH, then decide which to use.

Source A: Conversation markers (primary — captures iterations)

Find all ### LOADED SKILL: {name} markers in this conversation. For each marker, extract:

• The skill name (from the header)
• The description (from the **Description:** line)
• The body content (everything until the next --- separator or next ### LOADED SKILL: block)

This source preserves any iterations you made during the conversation. It's the happy path when conversation context is intact.

Source B: Installed plugins on disk

Run the discovery script to find skills-toolkit plugins already installed in this Cowork session:

bash "${CLAUDE_PLUGIN_ROOT}/skills/skills-save/scripts/discover-installed-plugins.sh"

Returns a JSON array of {pluginName, pluginRoot, manifestPath, skills: [{name, path, currentSha}]}. The script already filters for the skills-toolkit keyword and excludes plugins tagged iterated (those are already saved).

Cross-reference

For each Source B plugin, check whether ALL of its skill names appear in Source A's marker set. A full match means Source A's load was previously saved as that installed plugin. If no plugin matches the Source A skills, the user loaded but never clicked Save plugin.

Never claim a plugin is installed without running Source B. The discovery script is the only ground truth. Do not infer from context that the user clicked Save plugin — that's a hallucination.

Decide by case

Case A — markers present, matching installed plugin, some skills iterated. Use markers. Go to Step 2 to synthesize iterations. Save as iterated-{name} with the iterated keyword.

Case B — markers present, matching installed plugin, nothing iterated. Tell the user:

Already saved as {pluginName} ({N} skills, all unchanged). Nothing new to save. Reply snapshot to save anyway as a separate copy.

Wait. If snapshot, proceed with the Case A flow (iterated-* naming). Otherwise stop.

Case C — markers present, NO matching installed plugin (never clicked Save plugin). Tell the user:

Not installed yet. These skills came from /skills-load but Save plugin wasn't clicked. I can package them as {repo-name} now so you can install with one click. /skills-update will refresh them from upstream later.

Plugin name? (default: {repo-name})

After user confirms the name, go to Step 2 (in case they iterated despite not installing). In Step 4, use {repo-name} with NO iterated- prefix. In Step 5, DROP the iterated keyword AND include the repository field (find the https://github.com/... URL from the earlier /skills-load output in this conversation).

Case D — markers empty, installed plugins found (post-compaction fallback). Warn the user before proceeding:

Conversation markers not found — likely compacted. Falling back to {N} skills-toolkit plugins installed on disk. This saves the originals as an iterated-* plugin; any iterations from this conversation are NOT captured (the edit history was in the compacted span).

Found:

• {pluginName-1} ({M1} skills)
• {pluginName-2} ({M2} skills)

Save originals as iterated-* plugins? Reply yes, pick plugin names, or cancel.

If confirmed, for each chosen plugin read every {skill.path}/SKILL.md from disk. Skip Step 2's synthesis. Go to Step 3.

Case E — both empty.

No skills to save. No conversation markers AND no skills-toolkit plugins installed on disk.

Run /skills-load <github-url> first.

Stop.

Step 2: Synthesize current state (Source A only)

Skip this step entirely if Step 1 chose Source B — those are originals read from disk. They don't need synthesis.

For each Source A skill (from conversation markers), examine the conversation holistically to determine its CURRENT state:

• If the skill was discussed/modified/iterated on after the initial injection (e.g., user said "add a step for X", "reword the intro", "make it more concise"), produce the updated version that reflects those changes
• If the skill was not modified, use the original injected content verbatim

Track which skills were iterated and summarize what changed (high level — not a full diff, just enough for the user to confirm).

Step 3: Show the summary

Display a compact table with a Source column so the user can tell which skills came from conversation markers vs. the installed-plugin fallback:

Found {N} skills to save:

#	Skill	Source	Status	Notes
1	roadmap-planning	conversation	iterated	Added stakeholder-review step
2	discovery-process	conversation	unchanged	—
3	competitive-analysis	conversation	iterated	Reworded intro, added 2 criteria
4	positioning-workshop	conversation	unchanged	—

Save all {N} as a new plugin? Reply with a plugin name, all, or pick by number (1, 3).

When all skills come from Source B, the Source column shows installed plugin and the Status column shows original for every row (no iterations to display).

Step 4: Parse user response and plugin name

• Empty / all / yes → include all loaded skills
• Comma-separated numbers → include only selected
• Plugin name string → include all, use this as plugin name

Plugin name default depends on the Step 1 case:

• Cases A, B (snapshot), D: iterated-{repo-name} (e.g., iterated-product-manager-skills). Fallback if no repo known: iterated-skills.
• Case C (never installed): {repo-name} — no iterated- prefix, because this IS the plugin, not an iteration of one. Fallback: skills-from-conversation.

Sanitize the plugin name: kebab-case, [a-z0-9-] only. Reject empty names and re-ask.

Step 5: Build the .plugin file

Build the .plugin ZIP via Python inside the VM. Pass skill content as JSON (the content came from conversation markers in Source A, or from disk reads in Source B — the build step doesn't care which):

python3 << 'PYEOF'
import zipfile, json, os, glob

# ── Substitute these values from the /skills-save context ──
plugin_name = "<PLUGIN_NAME>"   # e.g., "iterated-product-manager-skills" or "geo-seo-claude"
skills_json = '<SKILLS_JSON>'   # JSON: [{"name": "...", "body": "..."}, ...]
is_iterated = <TRUE_OR_FALSE>   # True for Cases A/B/D, False for Case C
repository  = "<REPO_URL>"      # Case C: "https://github.com/owner/repo"; others: ""

# Cowork outputs dir lives at /sessions/<session>/mnt/outputs/ — discover it.
out_dirs = glob.glob('/sessions/*/mnt/outputs')
if not out_dirs:
    raise RuntimeError("Cowork outputs dir not found - is this a Cowork VM session?")
out_dir = out_dirs[0]
out = os.path.join(out_dir, plugin_name + '.plugin')

skills = json.loads(skills_json)

keywords = ["skills", "skills-toolkit", plugin_name]
if is_iterated:
    keywords.insert(2, "iterated")  # tells /skills-update to skip

manifest_dict = {
    "name": plugin_name,
    "description": "Skills saved from Cowork session",
    "version": "1.0.0",
    "author": {"name": "skills-toolkit"},
    "keywords": keywords,
}
if repository:
    manifest_dict["repository"] = repository  # Case C only — lets /skills-update refresh from upstream

with zipfile.ZipFile(out, 'w', zipfile.ZIP_DEFLATED) as zf:
    zf.writestr(".claude-plugin/plugin.json", json.dumps(manifest_dict, indent=2))
    for skill in skills:
        zf.writestr(f"skills/{skill['name']}/SKILL.md", skill['body'])

print(out)
PYEOF

Substitute actual values into the <PLACEHOLDER> slots above. skills_json is a JSON-encoded string of [{"name": "...", "body": "..."}, ...]. is_iterated is Python True for Cases A/B/D, False for Case C. repository is the GitHub URL for Case C, empty string for others.

Case C manifest: no iterated keyword, includes repository field. /skills-update will later find it via the skills-toolkit keyword and refresh it from the repo URL, same pattern as a fresh /skills-load.

All other cases: iterated keyword is present, no repository field — tells /skills-update to skip these (they have no upstream).

Step 6: Present the .plugin file to Cowork

Load mcp__cowork__present_files via ToolSearch, then call it with this exact shape — files is a list of objects, each with a single file_path key:

mcp__cowork__present_files(files=[{"file_path": "<output-path-from-python>"}])

The path MUST be the Linux path printed by the Python script above (under /sessions/<session>/mnt/outputs/). Windows-style paths and /outputs/ paths are rejected.

Cowork renders a rich preview with a "Save plugin" button. Clicking it installs the iterated plugin — distinct from the original GitHub-sourced plugin (they have different names if you used the default iterated-* prefix).

Step 7: Re-inject into conversation

Output the saved skills back into conversation so they remain accessible by name:

### LOADED SKILL: {skill-name}

**Description:** {description}

{Full synthesized body — do NOT truncate}

---

This keeps them usable immediately, even before the user clicks Save plugin.

Step 8: Report

Plugin {plugin-name} ready — {N} skills saved:

Skill	Status
roadmap-planning	iterated
discovery-process	unchanged (kept original)
competitive-analysis	iterated

Click "Save plugin" on the preview above to install. The skills will appear in your / menu immediately.

If an original /skills-load plugin is already installed, it stays untouched — this saves AS A SEPARATE PLUGIN named {plugin-name}.

If all skills came from Source B (installed-plugin fallback), add this note:

Heads-up: This plugin was built from the originals on disk because conversation markers were lost to compaction. To capture iterations next time, run /skills-save before the conversation gets long enough to compact — or redo your edits in a fresh conversation after reloading with /skills-load.

Edge cases

• No ### LOADED SKILL: markers in conversation: Go to Step 1's Case D (installed plugins on disk) or Case E (both empty). No plugin is built in Case E.
• Markers present but Source A's skills don't fully match ANY installed plugin: Case C — user never clicked Save plugin for this load. Offer to install via /skills-save with no iterated- prefix.
• Multiple /skills-load runs from different repos: Show a single table listing ALL found skills across sources. Let the user pick which to save. Offer "iterated-mixed" as a default name if sources differ.
• Name collision with existing plugin: If {plugin-name} matches an installed plugin, warn the user — Save plugin will replace it. Suggest a unique name or confirm the replace.
• Iteration detection unclear: Default to the most recent version discussed. If unsure, use the original injected content and flag as "unchanged (could not detect iteration)" in the table.
• present_files unavailable: Still re-inject into context (Step 7). Tell the user the .plugin file is at the path printed by the build script in the VM, or write it to the host via the Write tool for manual upload.
• Single loaded skill: Still package as a .plugin for consistency. The Save plugin flow works the same way.