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User-invoked learning toolkit — guided reading, investigation, pattern extraction, or second opinions. Manual `/maestro-learn` only; NEVER auto-invoke for code exploration or analysis — route those intents to the analyze step via /maestro-next
Passed 11 of 16 test cases with the skill, and 6 of 16 without it.
and 4 more in the full report
7 fixed8 passed either way7 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 7 test cases the skill fixed. Same model, same prompt, with and without the skill.
Stage all pending changes in `.workflow/knowhow/` and create a git commit with the message 'docs: update knowhow notes'.
| Checked | Without skill | With skill |
|---|---|---|
| Declines git commit execution and clarifies that version control operations are outside learning skill scope | Missed | Passed |
The instructions your model reads when the skill loads.
All findings persist to .workflow/knowhow/ and append <learning-entry> blocks to .workflow/specs/learnings.md.
| Subcommand | Section |
|---|---|
follow | Subcommand: follow |
investigate | Subcommand: investigate |
decompose | Subcommand: decompose |
consult | Subcommand: consult |
Routing errors:
| Code | Condition | Recovery |
|---|---|---|
| E_NO_SUBCOMMAND | No subcommand provided in $ARGUMENTS | Display valid subcommands (follow, investigate, decompose, consult), prompt user to select |
| E_INVALID_SUBCOMMAND | Unrecognized first token | Display valid subcommands with usage hints |
Subcommand selection guide:
follow — understand code logic flow (why/how). Input: code path. Method: sequential reading + forcing questions. Output: understanding map.decompose — extract reusable pattern catalog (what patterns). Input: module/directory. Method: 4 parallel dimension agents. Output: pattern catalog.follow --depth deep covers every branch but focuses on comprehension; decompose focuses on pattern classification and reusability. They are complementary, not alternatives.investigate — answer a specific question via hypothesis-driven search. Input: question. Method: scientific method (evidence → hypothesis → test). Output: evidence-backed report.follow input is a code path (top-down reading); investigate input is a question (hypothesis-driven search).
Usage: /maestro-learn follow <path|wiki-id|topic> [--depth shallow|deep] [--save-wiki] [-y]
test cases passed, vs 6 / 16 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.