Conciseness

The high-value material (recalc.py workflow, data_only warning, formulas-not-hardcodes rule, pitfalls checklist) is diluted by content Claude already knows: a hello-world openpyxl example ("sheet['A1'] = 'Hello'"), pandas basics ("df.head() # Preview data"), and basic openpyxl cell/formatting boilerplate. The error/verification material is also repeated across roughly five sections (Requirements for Outputs, Common Workflow step 6, Recalculating formulas, Formula Verification Checklist, Best Practices). Mostly useful but noticeably could be tightened — anchor 3 rather than anchor 4.

Actionability

Fully executable throughout: copy-paste-ready pandas/openpyxl snippets, a concrete command ("python scripts/recalc.py output.xlsx"), wrong-vs-right formula examples, and a precise JSON output spec for interpreting results. The common cases (read, analyze, create, edit, recalculate, verify) are each covered with runnable code — matches anchor 5.

Workflow Clarity

The Common Workflow is a clear 6-step sequence with an explicit validation checkpoint and feedback loop: "Recalculate formulas (MANDATORY IF USING FORMULAS)" → "If status is errors_found, check error_summary ... Fix the identified errors and recalculate again", plus a verification checklist — so it does not hit the missing-validation cap and exceeds anchor 4's gaps. It falls short of anchor 5 only because the workflow is fragmented across five overlapping sections with duplicate headings ("## Excel File Workflows" vs "## Common Workflow"), so no single coherent end-to-end sequence is presented.

Progressive Disclosure

Structure exists via headers and the scripts/recalc.py reference is real and clearly signaled (verified in the bundle), but ~285 lines are inlined monolithically: the financial-model color/number-formatting standards and the detailed recalc output documentation clearly belong in separate reference files, and reference-style content sits inline with no references/ directory at all. Anchor 3 ("content that should be separate is inline") fits better than anchor 4.

Specificity

Lists multiple specific concrete actions with comprehensive coverage: "open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats." This matches the anchor-5 example's breadth exactly, and the actions are domain-specific rather than generic.

Completeness

Both questions are answered explicitly: the "what" via the enumerated action list, and the "when" via "Use this skill any time a spreadsheet file is the primary input or output", "Trigger especially when the user references a spreadsheet file by name or path", plus negative triggers ("Do NOT trigger when the primary deliverable is a Word document..."). This exceeds anchor 4's "when could be more explicit" and matches anchor 5, including concrete trigger phrases.

Trigger Term Quality

Coverage is strong and includes file extensions (.xlsx, .xlsm, .csv, .tsv), "spreadsheet file", "tabular data", and a casual user phrasing ("the xlsx in my downloads"). However, the most common natural synonym — "Excel" (as in "Excel file"/"workbook") — never appears, so a few natural terms users actually say are missing, which fits anchor 4 rather than the fully comprehensive anchor 5.

Distinctiveness Conflict Risk

Clear niche (the deliverable must be a spreadsheet file) with distinct triggers and explicit disambiguation against adjacent skills: "Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved." This is stronger than anchor 4's minor-overlap example and matches anchor 5's minimal conflict risk.