Add full proposal system: DB schema (proposals + proposal_gaps tables),
CLI `ietf intake` command, and web UI with Quick Generate on /proposals/new.
The new page merges AI intake (paste URL/text → Haiku generates multiple
proposals auto-linked to gaps) with manual form entry. Generated proposals
are clickable cards that fill the editor below for refinement.
Uses claude_model_cheap (Haiku) for cost-efficient web intake. Includes
CaML-inspired draft proposals from arXiv:2503.18813 analysis.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Add /architecture page: system-of-systems view with 8 layers, component
cards, gap markers, source coverage chart, and clickable detail sidebar
- Give author clusters meaningful names from orgs + draft topic keywords
- Filter false positives (73 drafts, 54 ideas) from idea clusters,
architecture, ideas listing, and search results
- Add NIST source fetcher with curated catalog of 11 AI publications
- New pages: trends, complexity, sources, false positives, idea analysis
- Clickable gap cards with full details (evidence, priority, nearby work)
- Component detail panel with linked drafts and top ideas
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Tighten idea extraction prompts (1-4 ideas, no sub-features) reducing
1,907 ideas to 468 across 434 drafts (78% reduction)
- Add embedding-based dedup (ietf dedup-ideas) for same-draft similarity
- Add novelty scoring (ietf ideas score) and filtering (ietf ideas filter)
using Claude to rate ideas 1-5, removing 49 generic building blocks
- Final count: 419 high-quality ideas (avg 1.1/draft)
- Web UI: gap explorer with live draft generation and pre-generated demos
- Web UI: D3.js author collaboration network (498 nodes, 1142 edges,
68 clusters, org filtering, interactive zoom/pan)
- Academic paper: 15-page LaTeX workshop paper analyzing the 434-draft
AI agent standards landscape
- Save improvement ideas backlog to data/reports/improvement-ideas.md
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Python CLI tool that fetches AI/agent-related Internet-Drafts from the IETF
Datatracker, rates them using Claude, generates embeddings via Ollama for
similarity/clustering, and produces markdown reports.
Features:
- Fetch drafts by keyword from Datatracker API with full text download
- Batch analysis with Claude (token-optimized, responses cached in SQLite)
- Embedding-based similarity search and overlap cluster detection
- Reports: overview, landscape by category, overlap clusters, weekly digest
- SQLite with FTS5 for full-text search across 260 tracked drafts
Initial analysis of 260 drafts reveals OAuth agent auth (13 drafts) and
agent gateway/collaboration (10 drafts) as the most crowded clusters,
while AI safety/alignment is underserved with the highest quality scores.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
