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v0.11.0

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release: v0.11.0 — 4 phases via parallel sub-agents

Cuts v0.11.0 after P4+P5+P6+P7 all shipped through worktree-isolated
sub-agents. CHANGELOG.md v0.11.0 section documents per-phase commits,
sub-agent coordination notes (stale-base, dep-rejection, SLA breach),
and deferred wiring for v0.11.1.

Cargo.toml version 0.10.1 → 0.11.0.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

v0.10.1

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v0.10.1 — rust-vs-giants receita + /disky v2 wizard + baseline reseed

v0.10.0

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v0.10.0 — CLI-only surface · disky-mcp dropped

v0.9.0

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v0.9.0 — time-series + APFS sparse fix + /disky skill

Theme: precision disk-management via temporal/pattern analysis.

Major features:
- disky growth — per-dir Δ between two snapshots (added/grew/shrank/removed).
- disky growth --over <duration> — auto-pick oldest snapshot within window.
- disky churn --over <duration> — mtime-based per-dir activity heatmap.
  Identifies log generators and hot working directories.
- disky empty — files with size = 0.
- disky old --older-than <duration> — files past mtime cutoff.
- disky filter --where <predicate> + --json-input — pipe disky output
  through a small DSL (size > 1GB AND ext = 'log').
- @latest~N time-relative snapshot ref.

APFS sparse-file fix:
- Adds physical_size column (st_blocks * 512). Schema is additive.
- Global --physical flag flips top / dirs / ext / stats to physical
  bytes. OrbStack data.img drops from 8.8 TB reported → 13 GB actual.
  Total ~/ size: 8.08 TB logical → 99.21 GB physical, matching du -sh.

Claude Code skill:
- claude-skill/disky/SKILL.md + render.py — single .py FastHTML +
  Monster UI report renderer. Invoked by /disky.
- AGENTS.md defines Design Feel (paper/ink/rust/olive palette,
  Fraunces + Manrope, editorial brutalism).

Perf:
- idx_path + idx_name indices added at scan time. Cleanup query
  perf bug still open (79s+ on 1.77M-row snapshot) — deferred to
  v0.10.0; needs storage-model rework.

Tests: 71 fast-tier, all green. SCHEMA_VERSION still 1.

Commits since v0.8.0:
  feat(churn,growth): disky churn + growth --over <duration>
  feat(skill,perf): /disky skill + Design Feel + idx_path
  feat(scan): physical_size column
  feat(top): --physical flag
  feat(physical): wire --physical to dirs / ext / stats + render.py polish

v0.8.0

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v0.8.0 — composability + analysis foundation

Closes the v0.8.0 themes from docs/roadmap-v0.8-v0.12.md:

- feat(query): disky empty + disky old --older-than DURATION
- feat(growth): disky growth — per-directory Δ between two snapshots
- feat(filter): disky filter --where with --json-input chain mode

Composability arrives: `disky top --format json | disky filter --where "size > 1GB"`
is real, not aspirational.

70 fast-tier tests, all green. SCHEMA_VERSION still 1 (purely additive).
Inner test loop ~0.7s. 10k competitor bench: disky/dua = 3.27× (improving
from 3.62× at 1k as DuckDB fixed costs amortize).

BDD scenarios + benchmark catalog committed under features/ and benchmarks/.
Roadmap through v0.12.0 documented at docs/roadmap-v0.8-v0.12.md.

v0.7.0

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v0.7.0 — dev-loop foundation + config + forget + MCP annotations + me…

…trics infra

Highlights:
- chore(dev-loop): M0 fast test pyramid (60s→0.38s inner loop)
- feat(config): ~/.config/disky/config.toml + DISKY_* env
- feat(errors): RFC 9457 instance field
- feat(forget): restic-style snapshot retention
- feat(mcp): tool annotations + disky_discover + disky_forget
- feat(snapshots): @latest~N time-relative ref
- chore(metrics): collector + baseline + competitor bench scaffold

Baseline: metrics/baseline.json @ commit 1e441d3 on Apple M4.

v0.1.0

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feat: initial release — fast macOS disk analyzer

Full-featured CLI + TUI disk analyzer for macOS:
- Parallel filesystem traversal via jwalk (all CPU cores)
- DuckDB embedded storage with persistent snapshots
- ncdu-style interactive TUI via ratatui
- Batch Appender inserts (50k entries/batch)
- memchr SIMD extension extraction
- HTML cleanup report export
- Snapshot management (~Library/Application Support/disky/)
- CLI: scan, tui, top, dirs, ext, find, stats, list

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>