]" in READMEAn open source multi-tool for exploring and publishing data
INTEGRATE — Add datasette to the vault as the canonical tool for turning SQLite databases into explorable, API-served data products with a single CLI command.
20/24 — actively-maintained / adequately-documented / high-discipline
Failed: H6: FAIL — 597 open issues exceeds the 100-issue healthy threshold; reflects high user volume but indicates triage backlog
Passed:
H1: PASS — Latest release 1.0a30 tagged 2026-05-24
H2: PASS — Release 1.0a30 is 1 day old relative to appraisal date 2026-05-25
H3: PASS — Last commit 2026-05-24 (1 day ago)
H4: PASS — Last commit 2026-05-24 (within 30-day window)
H5: PASS — Archived: false
H7: PASS — Apache-2.0 license present
H8: PASS — CI badge "[]" in README
Failed: D5: FAIL — No README heading matching "API", "Configuration", "Options", "Reference", "Commands", or "Parameters" visible in the first 8KB D8: FAIL — No section headed "Limitations", "Caveats", "Known Issues", "Trade-offs", or "Not supported" found
Passed:
D1: PASS — README content is present and non-empty
D2: PASS — README is several KB, well above the 1000-byte threshold
D3: PASS — Explicit install instructions: "brew install datasette" and "pip install datasette"
D4: PASS — Code block datasette serve path/to/database.db demonstrates core usage
D6: PASS — First paragraph: "Datasette is a tool for exploring and publishing data. It helps people take data of any shape or size..." (within first 500 chars)
D7: PASS — External docs site https://docs.datasette.io/ linked in README
Failed: E1: FAIL — Primary language is Python, which is not in the typed-language list (TypeScript, Rust, Go, Java, Kotlin, C#, Swift, Scala, Haskell)
Passed: E2: PASS — package.json present in Dependency Manifest E3: PASS — 6 direct JS dependencies in package.json (well under 30 threshold); Python deps not enumerated but project is mature with known stable deps E4: PASS — CI Test badge in README references GitHub Actions Test workflow E5: PASS — 11,098 stars exceeds the 50-star threshold by a wide margin E6: PASS — ~103 months since creation (Oct 2017); 11098/103 ≈ 107.7 stars/month, far above the 2 stars/month threshold E7: PASS — 842 forks exceeds the 5-fork threshold E8: PASS — "An open source multi-tool for exploring and publishing data" is descriptive and >20 characters
| Dimension | Score | Assessment |
|---|---|---|
| Harvest Value | 1 | The automatic SQLite-to-API pattern and ASGI plugin architecture are well-established and well-documented, offering one or two readable patterns (plugin hooks, metadata-driven API generation) but nothing architecturally novel for PAI's design concerns in 2026. |
| Integration Readiness | 2 | Drop-in via pip install datasette or Homebrew; the CLI (datasette serve <db>) and JSON API work immediately against any SQLite file; Docker image available for containerized PAI deployments. |
| Overlap Risk | 0 | No repo in the vault covers SQLite exploration or automatic data API generation; crowding index is 0 and this is the first appraisal for this category. |
| Gap Fill | 0 | The landscape Gaps section does not flag SQLite data exploration or data publishing as a declared need; this is a capability addition rather than a gap closure for the current vault. |
Composite: 0.625
Category: SQLite Data Explorer Crowding: 0 repos in vault (first-in-category) Alternatives: first in this category vs. top alternative: N/A — datasette is the inaugural repo in this category Landscape impact: filling a gap — no data exploration or auto-API tool is currently represented in the vault
Density: 10/10 — All ten inputs available: repository metadata (name, description, topics, language, license, stars, forks, open issues, dates, archived flag), latest release info, README first 8KB, dependency manifest (package.json), landscape rolling summary, category breakdown, overlap clusters, gaps analysis, high-confidence picks table, and related prior appraisals; trend signals were noted as unavailable this run but all other inputs were present.
The 597 open issues is the one health flag worth watching; at datasette's community scale this is more a sign of high engagement than neglect (Simon Willison is an extremely active maintainer), but it warrants periodic re-check. The release version 1.0a30 indicates the project is still in alpha versioning for its 1.x line despite nearly a decade of production use — consumers should track the stable-vs-alpha API surface carefully before deep integration.