glebis/coaching-session-summarizer
coaching-session-summarizer/SKILL.md
This skill should be used to summarize coaching or therapy session transcripts after a Fathom/Granola sync. The agent analyzes the transcript itself (no API key, runs on the subscription) and appends key insights, decisions, action items, and trail connections. Supports quick extraction or deep analysis with cross-session pattern detection.
$ install --global
skillsauthnpx skillsauth add glebis/claude-skills coaching-session-summarizerInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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SKILL.md
- name:
- coaching-session-summarizer
- description:
- This skill should be used to summarize coaching or therapy session transcripts after a Fathom/Granola sync. The agent analyzes the transcript itself (no API key, runs on the subscription) and appends key insights, decisions, action items, and trail connections. Supports quick extraction or deep analysis with cross-session pattern detection.
Coaching Session Summarizer
Overview
Analyzes a coaching/therapy session transcript and appends a structured summary (key insights, decisions, action items, deep analysis, connected trails) to the note.
The agent (Claude Code) performs the analysis directly — reading the transcript and writing the summary in this session. There is no Anthropic API call and no billing; it runs entirely on the active subscription. A legacy API-based script is kept only as a headless fallback (see bottom).
When to Use This Skill
- A new Fathom/Granola transcript was synced to the vault (coaching or therapy)
- User asks to summarize/analyze a session (
/summarize-session [file]or similar) - After
calendar-syncor a Granola export, when a new*-coaching.md,*-therapy.md, or*-session.mdfile appears — offer to summarize it
Workflow (agent-driven — default)
Do this in-session with native tools. No API key required.
Step 1 — Gather context
Run the deterministic helper to get the transcript text, previous sessions, and the trail list in one shot:
python3 ~/.claude/skills/coaching-session-summarizer/scripts/gather_context.py \
<transcript-file> --vault ~/Brains/brain
It prints:
- Previous sessions with the same participant (paths) —
Readthese only in deep mode, for cross-session pattern detection - Available trails — pick 2–4 most relevant to link
- Session content — the summary + transcript to analyze (any prior AI-Generated Summary is stripped so re-runs stay clean)
Pass --participant <name-slug> if the filename doesn't encode the person
(e.g. Granola exports titled by topic): --participant gleb-kalinin.
Step 2 — Analyze
Read the session content and extract, in the analytical voice of a session analyst (objective, using the speaker's authentic language where it matters):
- Key Insights — 3–5 main realizations / breakthroughs / observations
- Decisions Made — concrete choices or commitments
- Action Items — specific next steps; prefix time-sensitive ones with
[URGENT]and scheduling items with[SCHEDULING] - Session Themes — 2–3 recurring topics or patterns
Deep mode (default for therapy and milestone sessions) — also Read the
previous sessions and add:
- Pattern Detection — themes recurring across sessions
- Progress Assessment — movement on earlier commitments
- Energy/Motivation Markers — shifts in energy, resistance, affect
- Potential Obstacles — what might block progress
Step 3 — Append with Edit
Append the summary to the end of the transcript file using Edit (never
overwrite existing content). Match this exact structure:
## AI-Generated Summary
*Generated: YYYY-MM-DD*
### Key Insights
- ...
### Decisions Made
- ...
### Action Items
- [URGENT] ...
- ...
### Session Themes
- ...
## Deep Analysis
- **Pattern Detection**: ...
- **Progress Assessment**: ...
- **Energy/Motivation Markers**: ...
- **Potential Obstacles**: ...
## Connected Trails
- [[Trails/Trail - <Name>|<Name>]]
- [[Trails/Trail - <Name>|<Name>]]
Use the current date (date +%Y-%m-%d) in the Generated line. Omit the Deep
Analysis section in quick mode. Verify trail link names against the printed
trail list — case and exact wording matter for Obsidian links.
Modes
- quick — Key Insights, Decisions, Action Items, Themes. Skip Deep Analysis and previous-session reads.
- deep (recommended for therapy / milestones) — everything, including reading previous sessions for pattern detection.
Integration with Sync
After calendar-sync or a Granola/Fathom export, check for new session files
(*-coaching.md, *-therapy.md, *-session.md). If one appears, offer:
"New session detected — summarize now?" Default to deep mode for therapy.
Notes
- Preserves the original transcript intact; the summary is always appended.
- Trail linking requires the
Trails/directory in the vault root. - Cross-session comparison works best with consistent naming:
YYYYMMDD-name-coaching.md/YYYYMMDD-name-therapy.md. - Re-running is safe:
gather_context.pystrips any prior AI-Generated Summary before printing, so the agent analyzes only the raw session. (Delete the old## AI-Generated Summaryblock from the file before re-appending if you want to replace rather than stack summaries.)
Resources
scripts/
- gather_context.py — (default path) deterministic context gatherer, no API. Prints transcript text + previous sessions + trail list for the agent to analyze in-session.
- summarize_session.py — legacy / headless fallback. Calls the Anthropic
API directly (model via
SUMMARIZER_MODEL, defaultclaude-sonnet-4-6) and bills a fundedANTHROPIC_API_KEY. Use only when no interactive agent is available (e.g. cron). Exits with a clear message if the key has no credit.
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