Pipeline refresh:
- Extract ideas from 46 remaining drafts (844 total ideas now)
- Clear stale llm_cache entries blocking re-extraction
- Re-run gap analysis with expanded corpus: 10 gaps (was 12), fresh IDs #1-#10
- Re-link 3 proposals to new gap IDs
- Add scripts/pipeline-refresh.sh for reproducible runs
Draft generation moved from gaps to proposals:
- Remove "Generate Internet-Draft" section from gap detail page
- Add it to proposal detail page instead (proposals → generate I-D flow)
- New route POST /proposals/<id>/generate with richer context
(proposal title + description + linked gap topics)
- Remove misleading "Search related drafts" link from gap page
(related drafts already shown inline)
Public page polish:
- Overview: update subtitle to mention all 6 standards bodies
- About: describe multi-source scope (IETF, ISO, ITU-T, ETSI, NIST, W3C)
- About: add guiding question ("Where is the AI agent standards race heading?")
- Obsidian export button hidden in production mode (prior commit)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Include data/drafts.db so other machines don't need to re-run
expensive Claude API calls (~$3+ of analysis, 474 drafts, 403 authors,
1262 ideas, 12 gaps). Add scripts/db-export.sh and scripts/db-import.sh
for portable compressed SQL dump sharing.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Add `ietf auto` command: fetches, analyzes, embeds, extracts ideas,
and refreshes gaps across all sources with cost-based auto-approval
- Fix SourceDocument→Draft conversion in auto fetch step
- Fix gap_analysis method name in auto command
- Process all 270 unrated ETSI/ISO/ITU/NIST drafts (761 total, all rated)
- Update web UI templates and data layer for multi-source support
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Release prep:
- Version bump to 0.3.0 (pyproject.toml, cli.py)
- Rewrite README.md with current stats (475 drafts, 713 authors, 501 ideas)
- Add CONTRIBUTING.md with dev setup and code conventions
Blog site:
- Add scripts/build-site.py (markdown → HTML with clean CSS, dark mode, nav)
- Generate static site in docs/blog/ (10 pages)
- Ready for GitHub Pages deployment
Academic paper (paper/main.tex):
- Update all counts: 474→475 drafts, 557→710 authors, 1907→462 ideas, 11→12 gaps
- Add false-positive filtering methodology (113 excluded, 361 relevant)
- Add cross-org convergence analysis (132 ideas, 33% rate)
- Add GDPR compliance gap to gap table
- Add LLM-as-judge caveats to rating methodology and limitations
- Add FIPA, IEEE P3394, W3C WoT to related work with bibliography entries
- Fix safety ratio to show monthly variation (1.5:1 to 21:1)
Pipeline:
- Fetch 1 new draft (475 total), 3 new authors (713 total)
- Fix 16 ruff lint errors across test files
- All 106 tests pass
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>
- Fixed W3C fetcher to paginate /specifications endpoint (group
endpoints use type prefixes like cg/, wg/ that weren't in config)
- Fetched 72 new IETF drafts + 1 W3C spec, all analyzed and embedded
- Regenerated dashboard with updated data
- Total: 434 docs, 11 gaps, 1907 ideas
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Includes all draft metadata, full text, Claude ratings (cached),
and nomic-embed-text embeddings. This is the expensive data —
~114k tokens of Claude analysis + 260 Ollama embeddings.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
