minutes-mirror
Self-coaching analysis of your own behavior across meetings — talk-time ratio, filler words, hedging language, monologue length, energy patterns, and (when meetings are tagged via /minutes-tag) what your behavior in winning meetings looks like vs losing ones. Use this whenever the user says "how did I do", "review my last meeting", "mirror", "self-review", "show my patterns", "coach me", "where am I weak", "talk time", "am I improving", "what do I do in meetings I win", "feedback on me", or asks for any kind of personal feedback on their own meeting behavior. This is the rare skill that gives
npx skills add silverstein/minutes --skill minutes-mirror --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
## Skill Path Before running helper scripts or opening bundled references, set: ```bash export MINUTES_SKILLS_ROOT="$(git rev-parse --show-toplevel)/.opencode/skills" export MINUTES_SKILL_ROOT="$MINUTES_SKILLS_ROOT/minutes-mirror" ``` # /minutes-mirror Self-coaching analysis based on your own meeting transcripts. Two modes: - **Single-meeting mode** — review a specific meeting and surface what you did, what was unusual for you, and one concrete thing to try next time. - **Pattern mode** — surface trends across the last 30 days, including (if meetings are tagged) what behaviors correlate with winning vs losing. The point is not to roast you. The point is to give you a kind, evidence-based mirror to behaviors that are usually invisible to you because you're inside them. ## How it works ### Phase 0: Identify "you" Mirror needs to know which speaker label in the transcript is the user. Real transcripts use one of two formats: - **Enrolled users**: `[Mat 0:00] Hey there.` — first-name labels from voice enrollment - **Non-enrolled users**: `[SPEAKER_0 0:00] Hey there.` — generic labels from diarization Either way, mirror needs to know which label maps to the user. Check sources in order:
- Skill Path
- How it works
- Phase 0: Identify "you"
- Phase 1: Pick a mode
- Phase 2a: Single-meeting analysis
- Phase 2b: Pattern mode
- Phase 3: Closing ritual
- Gotchas
export MINUTES_SKILLS_ROOT="$(git rev-parse --show-toplevel)/.opencode/skills" export MINUTES_SKILL_ROOT="$MINUTES_SKILLS_ROOT/minutes-mirror" minutes voices --json 2>/dev/null cat ~/.minutes/config/self.txt 2>/dev/null mkdir -p ~/.minutes/config printf '%s\n' <label1> <label2> ... > ~/.minutes/config/self.txt minutes list --content-type meeting --limit 5 set -o pipefail minutes get "<exact path>" | \ python3 "$MINUTES_SKILL_ROOT/scripts/mirror_metrics.py" \
What does the minutes-mirror skill do?
Self-coaching analysis of your own behavior across meetings — talk-time ratio, filler words, hedging language, monologue length, energy patterns, and (when meetings are tagged via /minutes-tag) what your behavior in winning meetings looks like vs losing ones. Use this whenever the user says "how did I do", "review my last meeting", "mirror", "self-review", "show my patterns", "coach me", "where am I weak", "talk time", "am I improving", "what do I do in meetings I win", "feedback on me", or asks for any kind of personal feedback on their own meeting behavior. This is the rare skill that gives
How do I install it?
Run `npx skills add silverstein/minutes --skill minutes-mirror --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From silverstein/minutes, a repository with 1,410 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.