# Continuous Learning > Extract repeated patterns from archived sessions and offer to convert them into reusable skills - **Type:** Skill - **Install:** `agentstack add skill-manastalukdar-ai-devstudio-continuous-learning` - **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior - **Seller:** [manastalukdar](https://agentstack.voostack.com/s/manastalukdar) - **Installs:** 0 - **Category:** [Agent Skills](https://agentstack.voostack.com/c/agent-skills) - **Latest version:** 0.1.0 - **License:** MIT - **Upstream author:** [manastalukdar](https://github.com/manastalukdar) - **Source:** https://github.com/manastalukdar/ai-devstudio/tree/main/skills/continuous-learning ## Install ```sh agentstack add skill-manastalukdar-ai-devstudio-continuous-learning ``` Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent. ## About # Continuous Learning Scan archived session logs to surface recurring manual workflows, then offer to convert high-frequency patterns into new SKILL.md stubs so repeated work becomes permanent automation. ## Usage ``` /continuous-learning # Scan all archived sessions for patterns /continuous-learning --min 2 # Lower threshold (default: 3 repetitions) /continuous-learning --generate # Auto-generate stubs without prompting ``` ## Behavior ### Phase 1: Discover sessions ```bash # Find all archived session files (not the active .current-session pointer) find .claude/sessions -name "*.md" -not -name ".current-session" 2>/dev/null | sort ``` If fewer than 3 session files exist, report "Not enough session history yet (need 3+)" and exit. ### Phase 2: Extract commands and workflows Scan each session file for lines that match invocation patterns: ```bash # Commands invoked (slash commands, skill names) grep -h -E "^/[a-z]|^\*\*Command\*\*:|Ran:|Invoked:" .claude/sessions/**/*.md 2>/dev/null \ | sed 's|.*: ||' | sort | uniq -c | sort -rn | head -40 ``` Also extract multi-step sequences: look for clusters of 3+ consecutive commands that appear together in at least `--min` sessions. ### Phase 3: Build pattern registry Load or create `.claude/cache/continuous-learning/patterns.json`: ```json { "last_scan": "2026-06-04T00:00:00Z", "patterns": [ { "commands": ["/security-scan", "/review", "/test"], "frequency": 5, "sessions": ["session-a.md", "session-b.md"], "candidate_name": "quality-gate" } ] } ``` Merge new findings with prior registry. Patterns that drop below `--min` threshold are removed. ### Phase 4: Present findings Display a ranked table of patterns that meet the threshold: ``` Repeated patterns found across your sessions: Rank Frequency Pattern ──── ───────── ─────────────────────────────────────────── 1 7x /security-scan → /review → /test 2 5x /find-todos → /fix-todos → /commit 3 4x /db-diagram → /migration-generate → /seed-data 4 3x /brainstorm → /write-plan → /implement Convert any of these to a skill? (enter rank, or 'none'): ``` ### Phase 5: Generate skill stub (if requested) For the chosen pattern, emit a SKILL.md stub using the skillify template: ```markdown --- name: description: disable-model-invocation: false risk: safe --- # ## Usage \`/\` ## Behavior 1. Run `/step-one` 2. Run `/step-two` 3. Run `/step-three` ## Token Optimization **Expected range**: 200–600 tokens (delegates to constituent skills) **Early exit**: Each constituent skill handles its own early exit. **Patterns used**: Delegation to existing skills ``` Save to `skills//SKILL.md` and confirm location to user. Do not commit. ## Examples **No patterns yet:** ``` /continuous-learning → Scanned 2 session files — need at least 3 to detect patterns. Run more sessions, then try again. ``` **Patterns found:** ``` /continuous-learning → Scanned 8 sessions. Found 3 repeated patterns (threshold: 3x). [table shown] Convert #1 to a skill? → User enters "1" → Stub written: skills/quality-gate/SKILL.md ``` ## Token Optimization **Expected range**: 400–900 tokens (initial scan), 150–300 tokens (cache hit) **Caching**: Stores pattern registry in `.claude/cache/continuous-learning/patterns.json`. On subsequent runs, only sessions newer than `last_scan` are re-processed; old results are merged from cache. **Early exit**: Exits immediately if fewer than 3 archived session files exist. **Patterns used**: Grep-before-Read (scan with grep, never read full session files into context), Bash for system queries, progressive disclosure (summary table before detail), early exit. ## Edge Cases - **No sessions directory**: Reports setup instructions and exits. - **Sessions with no command lines**: Skips those files silently. - **Candidate name collision with existing skill**: Appends `-2` suffix and warns user. - **User declines all patterns**: Exits cleanly with "Nothing converted." ## Safety - Never deletes or modifies existing skills or session files. - Skill stubs are written to `skills/` only — not installed to `~/.claude/skills/` automatically. - Does not commit anything; user must run `/commit` explicitly. ## Source & license This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code. - **Author:** [manastalukdar](https://github.com/manastalukdar) - **Source:** [manastalukdar/ai-devstudio](https://github.com/manastalukdar/ai-devstudio) - **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-manastalukdar-ai-devstudio-continuous-learning - Seller: https://agentstack.voostack.com/s/manastalukdar - 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%.