7ec4e5d121
Supersedes the previous commit's approach. Renaming harbor's four colliding
codes fixed one programme; tightening the matching rule fixes the rule, so a
room may be called anything. cr1/of/st1/st2 are restored and the examples are
byte-identical to their pre-§39 state -- which also means existing .dom
artefacts (evolved-3M*) stay valid, so migrate_ju3_rename.py is deleted.
The rule: Urb has exactly three GENERIC structural types (get_space_types:
qw/C O S/), the leaves the search creates. Measured across the corpus: 154 C,
110 O, 1 S, not one lowercase generic -- while every programme code is
lowercase, including single-character ones (r, t, m, n). Case is the
discriminator, not length. Every generic test was type[0].lower() in (...), a
case-insensitive PREFIX that swept up any programme code starting with those
letters; they now match the generic set exactly. 30 sites across dom, fitness,
graph, operators, programme, shapecurve and bubble.
NOT applied to the SEMANTIC prefixes: l/k/b/t classify programme codes by first
letter (graph.py builds bedroom<->toilet and kitchen<->living relations from
them) and stay prefix-based. Where the namespaces were mixed in one expression
they were split -- has_circulation's ("b","l","k","c") is three semantic
prefixes plus dom.is_circulation; access()'s ("l","c","s") is semantic l plus
the generic circulation set.
New: dom.GENERIC_{CIRCULATION,OUTSIDE,TYPES} + is_generic(); fitness.
_generic_class(), replacing the _t0 dispatch in quality_size/quality_width/
quality_proportion/value_rate -- the four terms that mattered most and that a
first sweep missed, since they dispatch through a t0 variable rather than an
inline test. graph._adjacency_target resolves a generic adjacency requirement
(programmes write "adjacency: [c, o]") to the generic set while every other
requirement keeps Perl's prefix semantics.
Two subtleties: S is in both generic sets but takes the OUTSIDE parameter
families -- a first translation tested circulation first and silently gave S
the circulation params, caught by test_get_space_params_sahn_proportion. And
validate_codes survives, narrowed to a code spelled exactly C/O/S, which is a
genuine ambiguity; merely starting with c/o/s is now fine.
Invariant asserted as a test: test_scoring_is_invariant_under_programme_code_
spelling relabels one tree and its config together and re-scores. Bit-identical
across 12 comparisons (6 seeds x collapse on/off).
Re-baseline (seed 1, 20k, original names): 58 fails (15 hard / 43 soft) against
the real 37-instance programme, with cr1 at 79.1 m2 vs declared 80 (was 32.9
and 17.1), of/st1/st2 all present and in band, and one fail naming any of them.
57 -> 58 on a 5-instance-harder programme is within noise: "did not regress".
Fallout (§39.5): 2g7.5's CP-SAT seeder win does not survive. Over 6 seeds --
harbor real 102/114 (cpsat loses), harbor old-effective 98/99 (tie, so the win
was already marginal), maple-court 156/144 (cpsat wins). maple is the control:
the solver did not regress, harbor's programme changed. Test xfail'd with that
reason plus a maple companion; both assign_solver flags stay default off.
Filed homemaker-py-w6x to re-check other narrow-margin harbor A/Bs.
345 passed, 1 xfailed, same 7 pre-existing fixture failures.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MJ84Feep79Hhm3E4zZJmnB
|
||
|---|---|---|
| .. | ||
| hooks | ||
| .gitignore | ||
| config.yaml | ||
| issues.jsonl | ||
| metadata.json | ||
| README.md | ||
Beads - AI-Native Issue Tracking
Welcome to Beads! This repository uses Beads for issue tracking - a modern, AI-native tool designed to live directly in your codebase alongside your code.
What is Beads?
Beads is issue tracking that lives in your repo, making it perfect for AI coding agents and developers who want their issues close to their code. No web UI required - everything works through the CLI and integrates seamlessly with git.
Learn more: github.com/steveyegge/beads
Quick Start
Essential Commands
# Create new issues
bd create "Add user authentication"
# View all issues
bd list
# View issue details
bd show <issue-id>
# Update issue status
bd update <issue-id> --claim
bd update <issue-id> --status done
# Sync with Dolt remote
bd dolt push
Working with Issues
Issues in Beads are:
- Git-native: Stored in Dolt database with version control and branching
- AI-friendly: CLI-first design works perfectly with AI coding agents
- Branch-aware: Issues can follow your branch workflow
- Always in sync: Auto-syncs with your commits
Why Beads?
✨ AI-Native Design
- Built specifically for AI-assisted development workflows
- CLI-first interface works seamlessly with AI coding agents
- No context switching to web UIs
🚀 Developer Focused
- Issues live in your repo, right next to your code
- Works offline, syncs when you push
- Fast, lightweight, and stays out of your way
🔧 Git Integration
- Automatic sync with git commits
- Branch-aware issue tracking
- Dolt-native three-way merge resolution
Get Started with Beads
Try Beads in your own projects:
# Install Beads
curl -sSL https://raw.githubusercontent.com/steveyegge/beads/main/scripts/install.sh | bash
# Initialize in your repo
bd init
# Create your first issue
bd create "Try out Beads"
Learn More
- Documentation: github.com/steveyegge/beads/docs
- Quick Start Guide: Run
bd quickstart - Examples: github.com/steveyegge/beads/examples
Beads: Issue tracking that moves at the speed of thought ⚡