WolfMarkDown v0.2.0

WolfMarkDown v0.2.0

WolfMarkDown now goes beyond valid Markdown formatting to recover clear document structure from messy pasted material.

Highlights

• Recovers latent headings, sibling sections, labelled lists, ordered steps, paragraphs, and comparison tables when source evidence is clear.
• Rebuilds GFM tables only when both column boundaries and a recognisable header row are present.
• Preserves ambiguity rather than inventing a table, heading, list, schema, or claim.
• Adds long-document handling with a document ledger and semantic handoff for cross-section reconciliation.
• Preserves protected technical identifiers and prevents unsafe publication of failed or unverified output.
• Adds synthetic regression coverage for structural recovery and conservative ambiguity preservation.
• Clarifies that a WolfMarkDown PASS is Markdown-quality evidence, not factual validation, policy approval, or publication authorisation.

Compatibility

WolfMarkDown is model-agnostic and works with Agent Skills hosts that load .agents/skills/wolfmarkdown or .claude/skills/wolfmarkdown.

Node.js 20+ is supported, including Node.js 22 and 24.

Verification

• 79/79 Node tests passing
• skills-ref validate ./wolfmarkdown passing
• Prettier, markdownlint, GFM parsing, protected-token integrity, and idempotence checks passing

Notes

Semantic repair remains agent-judged. WolfMarkDown provides the workflow, preservation rules, and deterministic proof; the host agent remains responsible for applying semantic judgement faithfully.

What's Changed

• docs: turn README into product landing page by @WolfMarkTools in #4
• fix: improve semantic structure recovery for pasted reports by @WolfMarkTools in #5

Full Changelog: v0.1.1...v0.2.0