v2.14.0 — contribution credits and runtime failure entry

Highlights

• Contribution credits and usage quota: Track lesson reads, enforce free quota (5/day anonymous, 20/day registered), manage credits from accepted contributions
• Contribution queue: Submit intake/lesson drafts with automatic redaction, dedup, and quality scoring
• Maintainer review CLI: Accept/reject contributions, grant credits, convert to lesson drafts
• Capture CLI: misaka capture --summary "error" --context log.txt for redacted failure reports
• GitHub Action capture: CI failure capture as artifacts (opt-in, no auto-publish)
• Feedback intake: search_knowledge.py --feedback for post-search feedback
• Demand board endpoint: GET /api/insights/demand-board for intake cluster visibility
• Trust semantics: Consistent indexed/published/verified definitions
• Runtime entry: Cursor failure-memory rule + Claude Code failure playbook + misaka run wrapper
• README rewrite: Single use case focus — "redacted failure-memory layer for AI coding agents"

New files

• scripts/usage_meter.py — Usage quota and credit management
• scripts/contribution_queue.py — Contribution queue with redaction and dedup
• scripts/contribution_review.py — Maintainer review CLI
• scripts/misaka_capture.py — CLI capture for redacted failure reports
• scripts/misaka_run.py — Command wrapper with MisakaNet search on failure
• .github/actions/misaka-capture/ — GitHub Action for CI failure capture
• .cursor/rules/misakanet-failure-memory.mdc — Cursor failure-memory rule
• docs/integrations/cursor-failure-memory.md — Cursor integration guide
• docs/integrations/claude-code-failure-memory.md — Claude Code failure playbook
• docs/trust-semantics.md — Trust level definitions