Ss skill discover

Discover, rank, and install Claude Code skills from GitHub, personalised to a local developer profile this skill builds and caches.

Modes

• Profile-only — triggered by "my profile" / "who am I" / "developer profile" / "coding habits". Run Step 1, present, stop.
• Discover (default) — Step 1 (cached) → Steps 2–4.

Step 1 — Load or build the profile

Cache lives at ~/.claude/user-profile.md (outside the repo, not git-tracked).

• Cache hit, Discover mode: read it, extract tech stack / interests / domains, proceed to Step 2.
• Cache hit, Profile-only mode: display, offer refresh / deep-dive / switch-to-discover.
• Cache miss or refresh: build via 1a–1f, then 1g.

1a — Prompt history (Agent)

Spawn a general-purpose Agent on ~/.claude/history.jsonl (each line: display, timestamp, project, sessionId). Ask it to report:

• Projects — unique paths, prompt counts, sorted.
• Time — date range, active days; infer local TZ from the sleep gap and report all hours in local time; activity by time-of-day and weekday; top 10 active days.
• Prompts — total, question/instruction ratio, length distribution (<50/50–200/200+), slash + bang commands with counts, top words and bigrams, tone/verbosity observations.
• Sessions — count, mean/median size, duration stats, top 5 longest with project + first prompt.
• Tech mentions — languages, frameworks, tools, platforms with counts.

1b — Insights data (if present)

Read ~/.claude/usage-data/report.html and any JSON under ~/.claude/usage-data/facets/. These give richer style/personality signal than raw history.

1c — Memory + project docs

Glob ~/.claude/projects/*/memory/MEMORY.md. For the top 10 projects from 1a, read {project}/CLAUDE.md if present. Read ~/.claude/settings.json for tool prefs and plugins.

1d — Git stats per top project

For each project that's a git repo:

git -C {project} remote -v 2>/dev/null | head -1
git -C {project} log --oneline -3 2>/dev/null
git -C {project} shortlog -sn --all --no-merges 2>/dev/null | head -3

Reveals solo-vs-team and recency.

1g — Synthesise and save

Synthesise into these dimensions: Tech Stack (languages, frameworks, dev tools — note uv/bun/ruff etc. — infrastructure), Project Portfolio (per project: domain, work vs personal, activity, solo vs team), Work Patterns (schedule in local TZ, session style, focus, weekday vs weekend), Communication Style (verbosity, tone, autonomy preference, slash-command power-user level), Personality Indicators (risk tolerance, builder vs user, learning style, customisation depth).

Write to ~/.claude/user-profile.md with sections: TLDR, Quick Summary, Tech Identity (table), Project Portfolio (table), Work Patterns, Communication Style, Personality Sketch, Raw Stats. Auto-save without asking. Display in chat.

In Profile-only mode, stop and offer: refine, deep-dive, or proceed to discover.

Privacy: all local; only reads existing Claude Code metadata (history, memory, settings — never transcripts or tool output); delete the file to forget.

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Step 2 — Parse args

$ARGUMENTS may contain a keyword, a number (max results, default 10), both, or neither. Extract them; if no keyword, leave it empty and let the script fall back to profile-based relevance scoring.

License filter defaults to permissive (MIT/Apache/BSD/ISC/Unlicense/0BSD); skills with restrictive or missing licences are excluded. Pass --no-license-filter only if the user explicitly asks.

Step 3 — Discover candidates

The search, fetch, license filter, dedupe, installed-skill filter, and ranking all live in scripts/discover.sh — one canonical pipeline shared with ssm-skill-weekly-discover and the weekly cron workflow. Call it:

scripts/discover.sh \
  --profile "$HOME/.claude/user-profile.md" \
  --limit "${MAX:-10}" \
  ${KEYWORD:+--keyword "$KEYWORD"} \
  --installed-dir skills \
  --exclude-repo JasonLo/skill-sommelier

Output is a JSON array sorted by (relevance, stars, pushed_at) descending, with {name, description, repo, path, stars, pushed_at, license, relevance, age_label} per element. Display as:

| # | Skill | Repository | Stars | Relevance | Description |

If the array is empty, report "no new skills found" and exit. If the script itself errors (network, missing gh/jq), surface its stderr verbatim — do not re-implement the pipeline inline.

Step 4 — Select and install

Ask via AskUserQuestion: install by number ("1, 3, 5" or "all"), view full SKILL.md, refine, or done.

For each selection, spawn a parallel Agent that:

1. Fetches SKILL.md and any sibling files from GitHub.
2. Enforces ss- prefix — if name doesn't start with ss-, prefix it (directory becomes skills/ss-{name}/, frontmatter name: updated). Tell the user: "Installing as ss-{name} per repo naming convention."
3. Saves to skills/{name}/SKILL.md (and references/ if present).

Security gate before save: list files; if any executables (.sh, .py, scripts/), show contents and require explicit approval. Otherwise proceed.

Report status per skill.

Errors

• Profile build fails (no history) → fall back to generic recommendations.
• <10 search hits → present what was found.
• 0 selected → exit gracefully.
• Per-skill install failure → report and continue with the rest.