# Session Reflect > Analyze a user's pi coding-agent session history for recurring behavior, prompting habits, workflow loops, friction, and preferences. Use when the user asks to inspect or reflect on pi sessions, common behavior patterns, agent/user interaction style, prompting habits, or personal pi workflow quality. - **Type:** Skill - **Install:** `agentstack add skill-dannote-dot-pi-session-reflect` - **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior - **Seller:** [dannote](https://agentstack.voostack.com/s/dannote) - **Installs:** 0 - **Category:** [Web & Browser](https://agentstack.voostack.com/c/web-and-browser) - **Latest version:** 0.1.0 - **License:** MIT - **Upstream author:** [dannote](https://github.com/dannote) - **Source:** https://github.com/dannote/dot-pi/tree/master/skills/session-reflect ## Install ```sh agentstack add skill-dannote-dot-pi-session-reflect ``` Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent. ## About # Session Reflect Use this skill to help the user understand their own pi usage patterns from local session logs. ## Data location By default this skill writes only to: ```text ~/.pi/agent/cache/session-reflect/ ``` It never writes analysis databases into the current project by default. Use `--db` only when the user explicitly asks for another location. Use `clean` to remove the default cache. The skill's job is **evidence retrieval + agent judgment**. Do not turn the helper script into the analyst. Use the script to load/search/query session evidence; use your own reasoning to infer patterns cautiously. ## Core rules - Discuss the analysis approach before implementing new tooling or making broad claims. - Do not hardcode English behavior categories or phrase lists as conclusions. - Treat repeated text, n-grams, FTS hits, and SQL aggregates as evidence leads, not interpretations. - Inspect surrounding context before interpreting short user turns like “go ahead” or “what next”. - Preserve multilingual text, typos, shorthand, pasted logs, and frustration markers as meaningful evidence. - Cite session paths or message keys for important claims. - Separate: observed facts, interpretations, confidence, alternative explanations, recommendations. - When the current user message is itself a high-signal intervention, follow the recovery protocol in `references/intervention-events.md` before continuing. ## Helper script Use `scripts/session-db.ts` as a local evidence workbench. It loads pi JSONL sessions into DuckDB and exposes SQL/search/context helpers. Install helper dependencies from the skill directory if they are missing: ```bash cd /skills/session-reflect npm install ``` Typical first step: ```bash npx tsx scripts/session-db.ts build ``` If the user points to another session root: ```bash npx tsx scripts/session-db.ts build --root ``` Useful evidence commands: ```bash npx tsx scripts/session-db.ts doctor npx tsx scripts/session-db.ts preset --list npx tsx scripts/session-db.ts preset overview npx tsx scripts/session-db.ts preset exact-short-repeats npx tsx scripts/session-db.ts preset long-sessions npx tsx scripts/session-db.ts turns --role user --limit 80 npx tsx scripts/session-db.ts turns --role user --short --limit 100 npx tsx scripts/session-db.ts ngrams --n 2 --min-count 3 --limit 50 npx tsx scripts/session-db.ts ngrams --n 3 --min-count 3 --limit 50 npx tsx scripts/session-db.ts search "literal or fuzzy lead" --role user --limit 25 npx tsx scripts/session-db.ts context --before 4 --after 8 npx tsx scripts/session-db.ts context --before 4 --after 8 --compact --hide-tools npx tsx scripts/session-db.ts examples --text "Go ahead." --limit 5 --before 3 --after 5 npx tsx scripts/session-db.ts sample --turns 5 --examples 2 --before 3 --after 5 npx tsx scripts/session-db.ts interventions --limit 30 --min-score 2 --sort score npx tsx scripts/session-db.ts interventions --limit 30 --min-score 2 --sort recent npx tsx scripts/session-db.ts interventions --signal autonomy_boundary,evidence_challenge --limit 20 npx tsx scripts/session-db.ts interventions --project quackdb --since 2026-06-01 --limit 20 npx tsx scripts/session-db.ts interventions --sample --limit 10 --min-score 2 npx tsx scripts/session-db.ts interventions --pasted include --limit 20 --min-score 2 npx tsx scripts/session-db.ts interventions --pasted only --limit 20 --min-score 2 npx tsx scripts/session-db.ts interventions --context --limit 10 --min-score 2 --sort recent --before 4 --after 6 npx tsx scripts/session-db.ts sql "select ..." ``` Use `--format table|json|markdown` before the subcommand when output will be read by the agent or quoted in a report: ```bash npx tsx scripts/session-db.ts --format markdown preset exact-short-repeats npx tsx scripts/session-db.ts --format json context ``` Read [references/query-cookbook.md](references/query-cookbook.md) when selecting SQL queries. Read [references/reflection-protocol.md](references/reflection-protocol.md) before producing a user-facing reflection. Read [references/intervention-events.md](references/intervention-events.md) when analyzing shouting, profanity, corrections, frustration, stop/pause requests, evidence challenges, or any high-signal user redirect. ## Recommended workflow 1. Clarify scope: recent sessions vs all sessions, coding-only vs all pi use, desired output depth. 2. Build or refresh the DuckDB evidence database with `scripts/session-db.ts build`. 3. Run a bounded first-pass evidence set: `overview`, `exact-short-repeats`, `tools`, `long-sessions`, and `sample --turns 3 --examples 2`. Add n-grams only when exact repeats do not explain enough. 4. Pick surprising evidence leads and retrieve compact context windows around representative message keys. For repeated exact turns, use `examples --text ...` for targeted sampling or `sample` for time-spread examples across top repeated turns. Use `--compact --hide-tools` first; rerun without them only when tool output matters. 5. For friction analysis, treat candidate events as broad **interventions**, not just profanity/escalation. Use `references/intervention-events.md` before generalizing. 6. Run targeted searches for explicit current-user preferences mentioned in the conversation, then inspect context. 7. Reason manually from evidence; do not let preset names, query names, repeated phrases, profanity, or all-caps become conclusions. 8. Present a concise reflection with citations and confidence levels. 9. Ask whether the user wants tooling changes, pi prompt/default changes, or deeper follow-up analysis. ## Output shape Use this structure unless the user asks otherwise: ```markdown # Pi session behavior reflection ## Evidence inspected - Database/session scope - Query types used ## Observed patterns For each pattern: - Observation - Evidence - Interpretation - Confidence - Alternative explanation ## Friction / failure modes ## Preferences inferred from behavior ## Recommendations to test ## Open questions ``` ## Source & license This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code. - **Author:** [dannote](https://github.com/dannote) - **Source:** [dannote/dot-pi](https://github.com/dannote/dot-pi) - **License:** MIT Install and usage instructions live in the source repository linked above. ## Pricing - **Free** — Free ## Security capabilities Automated source analysis of v0.1.0 — what this tool can access: - **Network access:** no - **Filesystem access:** no - **Shell / process execution:** no - **Environment & secrets:** no - **Dynamic code execution:** no *"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.* ## Versions - **0.1.0** — security scan: passed — Imported from the upstream source. ## Links - Listing page: https://agentstack.voostack.com/l/skill-dannote-dot-pi-session-reflect - Seller: https://agentstack.voostack.com/s/dannote - Browse the marketplace: https://agentstack.voostack.com/browse --- Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.