--- name: dx-pattern-extract-b293c0fada78 description: Scan completed tickets for recurring patterns and promote to cross-ticket knowledge. Run periodically or after completing several tickets. Creates .ai/graph/nodes/patterns/ entries. when_to_use: "Use when scanning completed tickets for recurring patterns. Trigger on 'extract patterns', 'promote patterns', 'find recurring patterns', 'update cross-ticket knowledge', or 'run pattern extraction'." argument-hint: "[--dry-run (preview without writing)]" disable-model-invocation: true model: haiku effort: low allowed-tools: ["read", "search", "write"] --- You scan all completed spec directories for recurring decisions and approaches, then promote patterns that appear in 3+ tickets to `.ai/graph/nodes/patterns/` for cross-ticket knowledge reuse. ## 1. Scan Decision Sources Collect decisions from two sources — structured YAML (preferred) and markdown fallback. ### 1a. Decision Nodes (primary source) Scan for structured decision YAML files: ```bash find .ai/graph/nodes/decisions/ -name "*.yaml" -type f 2>/dev/null ``` Read `shared/decision-schema.md` for the schema definition. For each decision YAML file, extract: - `ticket` — the work item ID - `chosen` — what was chosen - `tags` — for grouping by similarity - `files` — for matching by file overlap - `alternatives` — the rejected options (useful for understanding the pattern's scope) - `status` — skip decisions with `status: superseded` or `status: rejected` ### 1b. Implement.md fallback (for pre-Phase 4 tickets) Find all spec directories with completed work: ```bash find .ai/specs/ -name "implement.md" -type f 2>/dev/null ``` For each `implement.md` found, check if decision YAML files already exist for that ticket (by matching the ticket ID from the spec directory name against `.ai/graph/nodes/decisions/-*.yaml`). If YAML files exist, **skip the markdown scan** for that ticket — the YAML is the authoritative source. For tickets without decision YAML files, read from `implement.md`: - The `## Key Decisions` section (if present) — these are explicit design choices with alternatives - The `## Approach` section — the overall strategy - The `## Steps` section — scan step titles and file references for recurring patterns Also read `research.md` from the same directory (if present): - The `## Existing Implementation Check` section — which existing code was reused - The `## Key Findings` section — important discoveries Skip spec directories that have no `implement.md` or where all steps are still `pending` (ticket not yet worked on). ## 2. Identify Recurring Patterns Group the extracted decisions and approaches by similarity. Two decisions are "the same pattern" when they share: - **Same architectural choice** — e.g., "extend existing component" appears in multiple tickets - **Same file/class pattern** — e.g., multiple tickets modify the same utility or follow the same model class pattern - **Same technology approach** — e.g., multiple tickets use the same library, config pattern, or API pattern **Matching heuristics:** - Decisions that share `tags` values (from YAML) or reference the same files or directories - Decisions with the same `chosen` approach (from YAML) or "Chosen" text (from markdown), even if wording differs - Decisions with overlapping `files` lists (from YAML) — strong signal of the same pattern - Steps that follow the same sequence (e.g., "modify model → update dialog → update template") - Reused utilities or services that appear in 3+ tickets' Key Findings **Minimum threshold:** A pattern must appear in **3 or more tickets** to be promoted. Fewer occurrences may be coincidence. ## 3. Check Existing Patterns Read all existing pattern files: ```bash find .ai/graph/nodes/patterns/ -name "*.yaml" -type f 2>/dev/null ``` For each existing pattern: - Check if new tickets should be added to its `tickets:` list - Update `updated:` timestamp if new evidence found - Do NOT create duplicates — merge into existing patterns ## 4. Write Pattern Nodes Read `shared/pattern-schema.md` for the YAML schema. Create the directory if it doesn't exist: ```bash mkdir -p .ai/graph/nodes/patterns ``` For each newly identified pattern (3+ tickets, not already captured): 1. Generate a kebab-case topic slug from the pattern title 2. Write `.ai/graph/nodes/patterns/.yaml` following the schema exactly 3. Set `confidence: medium`, `trust_tier: long-term` 4. Include all tickets that contributed to the pattern For existing patterns with new ticket evidence: 1. Read the existing YAML 2. Add new ticket entries to `tickets:` 3. Update `updated:` timestamp 4. If tickets count reaches 5+, consider upgrading `confidence` to `high` ### Dry Run Mode If `--dry-run` is passed as argument: - Print what patterns would be created/updated - Do NOT write any files - Useful for previewing before committing to the graph ## 5. Present Summary ```markdown ## Pattern Extraction Complete **Specs scanned:** **Patterns found:** new, updated ### New Patterns | Pattern | Tickets | Tags | |---------|---------|------| | | <count> | <tags> | ### Updated Patterns | Pattern | New Tickets Added | Total | |---------|------------------|-------| | <title> | +<count> | <total> | ### Below Threshold (2 tickets — watching) | Candidate | Tickets | Notes | |-----------|---------|-------| | <description> | <count> | Needs 1 more occurrence | ### Next steps: - Patterns are now available for `/dx-plan` to reference - Run `/dx-plan <id>` — it will check patterns automatically - Review patterns in `.ai/graph/nodes/patterns/` for accuracy ``` ## Examples ### First extraction (bootstrapping) ``` /dx-pattern-extract ``` Scans 12 completed specs, finds 3 patterns with 3+ ticket occurrences each. Creates `.ai/graph/nodes/patterns/` with 3 YAML files. Reports 2 candidates below threshold. ### Dry run preview ``` /dx-pattern-extract --dry-run ``` Same analysis but only prints what would be created. No files written. ### Incremental update ``` /dx-pattern-extract ``` After completing 5 more tickets, re-run. Finds 1 new pattern, updates 2 existing patterns with new ticket evidence. Reports updated totals. ## Rules - **3-ticket minimum** — never promote a pattern with fewer than 3 occurrences - **No speculation** — only extract patterns from actual completed work, not hypothetical approaches - **Merge, don't duplicate** — if a pattern already exists, add ticket evidence to it - **Concrete, not abstract** — patterns must reference specific files, classes, or config keys. "Use existing utilities" is too vague; "Extend `validateField()` in `src/core/scripts/libs/forms.js`" is concrete. - **Tags for matching** — include enough tags that dx-plan can find relevant patterns by keyword matching against research.md - **Preserve provenance** — each ticket entry records HOW that ticket used the pattern, not just that it did - **Idempotent** — running twice produces the same result (no duplicate patterns or ticket entries) --- Source attribution: easingthemes Original project: https://github.com/easingthemes/dx-aem-flow/blob/f742d0c3bf54b6a4c7dfb9a60b5bd6257b492b65/plugins/dx-core/skills/dx-pattern-extract/SKILL.md License: MIT License information: https://opensource.org/license/mit Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice MIT License Copyright (c) 2025-2026 Dragan Filipovic Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. # Mega AI Hub resource metadata Creator / publisher: easingthemes Original project: https://github.com/easingthemes/dx-aem-flow/blob/f742d0c3bf54b6a4c7dfb9a60b5bd6257b492b65/plugins/dx-core/skills/dx-pattern-extract/SKILL.md Attribution basis: Source repository record Fields of work: Data & Analytics, Operations, Product Management Roles: Business Process Analyst, Data Analyst, Product Manager Specialties: Backend Tools: Markdown, Yaml Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: 19c7b9f5c92546eea55aab8522f08b0adf0072227f4e46e53153c53c6f525777