📚 A zero-dependency, git-backed micro-lesson library for AI Agents to asynchronously share and search verified debugging experience. | https://misakanet.org
This week focused on stability fixes, particularly addressing multiple instances where submissions and lesson content were being silently truncated at 2,000 characters in the worker intake path. The team also resolved numerous documentation inconsistencies—syncing Japanese README to English,…
Get this in your inbox every Monday →A deterministic 0–100 hygiene score — README, license, CI, tests, docs, and freshness.
Who ships this repo — author concentration and the bus factor across the last 300 mainline commits.
How welcoming this repo is to contributors — issue throughput, close time, responsiveness, and good-first-issue count.
What this project is built on — dependency count by ecosystem, the license mix, and anything worth a legal look before you adopt it.
Whether this project's CI can be trusted — pass rate, run times, flaky runs, and which workflow is the weak link.
Grounded in MisakaNet's README, structure, and recent commits — answers won't invent code they haven't seen.
A Monday email with what shipped, in plain English — no account needed.
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chore: auto-update lessons.json, public counts and generated pages (#2935)
fix(integrations): render the lesson's domain, not a field that does not exist (#2931)
fix(deps): bump sharp override to 0.35.5 — librsvg CVE-2026-96889 (#2927)
Two defaults that could not work, and a table row that named only one cause (#2926)
A floor, not a guess: counts only commits whose author, co-author trailer, or message explicitly credits an AI tool (Claude, Copilot, Cursor, aider, Codex…). Based on 30 mainline commits. Unattributed AI code isn't counted here — the full audit estimates that separately.
