Create, update, query, and validate YAML+Markdown tracking artifacts.
npx skills add https://github.com/miethe/deal-brain --skill artifact-tracking
Please help me install this Agent Skill. Skill: artifact-tracking Source: https://github.com/miethe/deal-brain/tree/main/.claude/skills/artifact-tracking Command: npx skills add https://github.com/miethe/deal-brain --skill artifact-tracking
This Skill enables AI agents to create, update, query, and validate AI-optimized tracking artifacts (progress files, context notes, bug fixes, observation logs) in a hybrid YAML+Markdown format that reduces token usage by up to 95% and makes data programmatically queryable.
Create a new Phase 1 progress file at .claude/progress/[prd]/phase-1-progress.md using the artifact-tracking templates; then use the included scripts to validate and migrate.
High-intent search queries and answers about installing and using this skill.
Hybrid YAML+Markdown format reduces token consumption by 95-99% by storing structured metadata in YAML frontmatter and prose in Markdown, enabling precise queries without loading full documents. Create phase progress files using the artifact-tracking templates, then query specific fields programmatically.
Use artifact-tracking to generate YAML+Markdown progress files for each phase with strict schema validation. Update task statuses, blockers, and context through field-level edits without rewriting entire files, then validate against jsonschema to ensure data integrity.
Yes, artifact-tracking includes Python migration tools to convert legacy Markdown into YAML+Markdown hybrid format. The process applies schema-driven validation and preserves content while enabling surgical field-level updates and token-efficient queries.
Artifact-tracking works with YAML frontmatter and Markdown body format for progress, context, bug-fix, and observation files. PyYAML and jsonschema validate structure; python-dateutil handles timestamps for seamless session handoff reports and artifact queries.
The embedded artifact-validator component enforces strict YAML frontmatter schemas using jsonschema. Run validation to check field compliance, detect missing blockers or context, and ensure hybrid format artifacts meet PRD-driven phase requirements before handoff.
Use hybrid format when you need programmatic queries, surgical field updates, or strict schema enforcement across multiple AI phases. Plain Markdown suits narrative-only content; hybrid format optimizes token efficiency and enables automated status queries and blocker detection.
rodmena-limitedOptimize data formats for LLM communication with TOON encoding and JSON/YAML serialization.
rbtkhnPackage AI work sessions into structured handoff summaries with decisions, risks, and next steps.
pradyumnasagarGuide authors through creating and validating ORS SKILL.md files.
tomwangowaParse Markdown work logs to track TODOs, decisions, and timeline events.
