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| author | Craig Jennings <c@cjennings.net> | 2026-05-24 17:01:40 -0500 |
|---|---|---|
| committer | Craig Jennings <c@cjennings.net> | 2026-05-24 17:01:40 -0500 |
| commit | 5886697b1485f00133065e8dd1e809fe854cd773 (patch) | |
| tree | 5f2bb7b88268b405685a0b7bd6ff41d831e691ca /modules/lorem-optimum.el | |
| parent | 79d9e1b58cd3cdb78b5347b72ed8e96f383cbc25 (diff) | |
| download | dotemacs-5886697b1485f00133065e8dd1e809fe854cd773.tar.gz dotemacs-5886697b1485f00133065e8dd1e809fe854cd773.zip | |
docs(load-graph): classify remaining domain and optional modules
Final classification batch: the last 19 modules — linear-config, local-repository, lorem-optimum, mail-config, markdown-config, music-config, pdf-config, quick-video-capture, reconcile-open-repos, restclient-config, slack-config, system-commands, telega-config, tramp-config, transcription-config, video-audio-recording, vterm-config, weather-config, wrap-up. I annotated each header, added a Batch 9 table to the inventory, and extended the validation allowlist. 101 of 102 modules are now classified; only elfeed-config remains, deferred on its test fix.
Two more hidden dependencies turned up. video-audio-recording uses the boundp shim for its C-; r binding, and mail-config registers C-; e directly without requiring keybindings, so it errors standalone rather than degrading. Both recorded for Phase 2.
Diffstat (limited to 'modules/lorem-optimum.el')
| -rw-r--r-- | modules/lorem-optimum.el | 10 |
1 files changed, 10 insertions, 0 deletions
diff --git a/modules/lorem-optimum.el b/modules/lorem-optimum.el index a6bec6576..8aa963456 100644 --- a/modules/lorem-optimum.el +++ b/modules/lorem-optimum.el @@ -7,6 +7,16 @@ ;; URL: https://github.com/yourname/cj-lipsum ;;; Commentary: +;; +;; Layer: 4 (Optional). +;; Category: O/L. +;; Load shape: eager. +;; Eager reason: none; placeholder-text generator, a command-loaded deferral +;; candidate. +;; Top-level side effects: none. +;; Runtime requires: cl-lib. +;; Direct test load: yes. +;; ;; Generate pseudo-Latin placeholder text using a simple order-two ;; Markov chain. You can train the chain on region, buffer, or file. ;; By default, it learns from a bundled Latin wordlist, which you can |
