Christian Nennemann
e7527ad68e
Critical fixes:
- Fix rating clamp range 1-10 → 1-5 (actual scale)
- Add `ietf ideas convergence` command (SequenceMatcher at 0.75 threshold)
- Fix "628 cross-org ideas" → 130 (verified from current DB) across 8 files
Security fixes:
- Sanitize FTS5 query input (strip special chars + boolean operators)
- Add rate limiting (10 req/min/IP) on Claude-calling endpoints
- Change <path:name> → <string:name> on draft routes
Codebase fixes:
- Add Database context manager (__enter__/__exit__)
- Wire false_positive filtering into queries (exclude by default in web UI)
- Fix Post 3 arithmetic ("~300" → "~409" distinct proposals)
Content & licensing:
- Add MIT LICENSE file
- Add IPR/FRAND notes (BCP 79, RFC 8179) to Posts 03 and 07
- Qualify "4:1 safety ratio" with monthly variation in 6 remaining files
- Add "Data as of March 2026" freeze-date headers to all 10 blog posts
- Hedge causal language in Post 04
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
93 lines
3.8 KiB
Markdown
93 lines
3.8 KiB
Markdown
# IETF Draft Analyzer — Project Instructions
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## What This Is
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Python CLI tool (`ietf`) to track, categorize, rate, and map IETF Internet-Drafts on AI/agent topics. 361 drafts, 403 authors, 1,262 ideas, 12 gaps. Uses Claude for analysis, Ollama for embeddings, SQLite for storage.
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## Key Paths
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- Source: `src/ietf_analyzer/`
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- Database: `data/drafts.db` (NOT `data/ietf_drafts.db`)
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- Reports: `data/reports/`
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- Blog series: `data/reports/blog-series/`
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- Agent definitions: `.claude/agents/`
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- Team prompt: `scripts/agent-team-prompt.md`
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- Scripts: `scripts/`
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## Development Journal
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**Every agent and every session MUST log development milestones to `data/reports/dev-journal.md`.**
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This journal serves two purposes:
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1. Track progress across sessions so nothing gets lost
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2. Source material for the meta blog post about using Claude agent teams to build this project
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### What to Log
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Append entries in this format:
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```markdown
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### [DATE] [AGENT/SESSION] — [SHORT TITLE]
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**What**: [What was done — features built, analyses run, posts written]
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**Why**: [The reasoning or decision behind it]
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**Result**: [Outcome, key numbers, links to artifacts]
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**Surprise**: [Optional — anything unexpected, a lesson learned, a tool limitation hit]
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**Cost**: [Optional — API tokens, time taken, model used]
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```
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### Examples of What to Log
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- Pipeline runs (how many drafts processed, cost, any failures)
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- New features implemented (what, why, how it changed the analysis)
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- Blog posts drafted or revised (key editorial decisions)
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- Architectural decisions (why we structured something a certain way)
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- Agent coordination moments (when one agent's output changed another's direction)
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- Surprises in the data (unexpected findings that shifted the narrative)
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- Tool/infra issues (things that broke, workarounds found)
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### What NOT to Log
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- Routine file reads or searches
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- Minor formatting fixes
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- Anything already captured in git commits
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## Agent Team Conventions
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When working as a team:
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1. **Architect** designs the narrative arc and reviews everything for coherence
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2. **Analyst** runs the pipeline, queries the DB, provides data packages
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3. **Coder** implements new features following existing patterns (Click CLI, SQLite, rich output)
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4. **Writer** produces the blog series from data packages and architectural guidance
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**Always launch agents in parallel when possible.** If agents have independent tasks (e.g., Analyst querying data while Writer drafts from existing material, or Coder implementing features that don't depend on each other), spawn them concurrently in a single message rather than sequentially. Only run agents sequentially when one genuinely depends on another's output.
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All agents should:
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- Read `scripts/agent-team-prompt.md` for the full brief
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- Log milestones to `data/reports/dev-journal.md`
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- Write blog posts to `data/reports/blog-series/`
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- Save reusable scripts to `scripts/`
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- Follow existing code patterns (don't over-engineer)
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## Blog Series
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7 posts planned in `data/reports/blog-series/` (01 through 07), plus:
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- **Post 8: "Agents Building the Agent Analysis"** — Meta post about using Claude Code agent teams to analyze and write about IETF agent standards. The dev-journal.md is the source material for this post.
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## Code Conventions
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- CLI: Click commands in `cli.py` with `@click.option()` decorators
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- DB: Tables in `db.py` `ensure_tables()`, queries as methods on `DraftDB`
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- Reports: Report types in `reports.py` `generate_report()`
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- Always cache Claude API calls via `llm_cache` table
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- Use `rich` for console output
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- Save multi-step workflows as scripts in `scripts/`
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## Current Status (2026-03-03)
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- v0.2.0, 361 drafts (101 new, unprocessed)
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- 101 new drafts need: analyze, authors, ideas, embed, gaps
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- Blog series: planned, not yet written
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- Agent team: defined in `.claude/agents/`, ready to launch
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