Initial phase-1 baseline of the karpathy/autoresearch-style loop. The formatter module is the inner-loop artifact; parser and linter are infra. The linter carries a LINTER_VERSION hash (v0.2.0) that will force a re-baseline on any rule change. Components: - harness/diff.py: case-sensitive field-level substring diff - harness/score.py: three-axis scoring (field, linter, canary exact) - src/cmos/linter.py: 9 CMOS 18 structural rules, each Purdue/CMOS cited - src/cmos/parser.py: locate ## Bibliography section, split entries - src/cmos/formatter.py: prompt + OpenAI call with caller injection - src/cmos/cli.py: cmos format path/to/draft.md - scripts/run_loop.py: loop runner with --fake mode for no-API runs - exemplars/: 3 canary seed exemplars (book, journal w/DOI, web), sourced from chicagomanualofstyle.org quick guide Tests: 48 passing. Fake-mode baseline scalar = 0.000 on the 3 seed exemplars (identity caller fails the linter on every rule). This is the floor the real GPT-5 formatter needs to improve from.
16 lines
663 B
TOML
16 lines
663 B
TOML
# Source: CMOS official citation guide (chicagomanualofstyle.org), 18th ed.
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# The canonical output is the guide's reference example verbatim.
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# Rule cited: CMOS 14.30 — place of publication no longer required in 18th ed.
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source = "CMOS official citation guide (chicagomanualofstyle.org/tools_citationguide/citation-guide-1.html)"
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type = "book"
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tags = ["book", "single-author"]
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canary = true
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messy_input = "yu, charles. interior chinatown. New York: Pantheon Books, 2020."
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expected_bibliography = "Yu, Charles. *Interior Chinatown*. Pantheon Books, 2020."
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[canonical]
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author = "Yu, Charles"
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title = "Interior Chinatown"
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publisher = "Pantheon Books"
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year = 2020
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