Conciseness

The body is mostly command-and-code without padded prose, but it includes unnecessary material: basic openpyxl/pandas getting-started code ('sheet["A1"] = "Hello"', 'df.head() # Preview data') that re-teaches libraries Claude already knows, and three overlapping checklists ('Formula Error Prevention', 'Formula Verification Checklist', 'Common errors to fix') that repeat the same pitfalls (#REF!, #DIV/0!, edge cases, wrong references). This matches the 3 anchor ('mostly efficient but includes some unnecessary explanation or could be tightened') rather than 4, since the duplication and tutorial-level examples exceed 'minor instances of over-explanation'.

Actionability

Guidance is fully executable: copy-paste-ready pandas and openpyxl snippets for reading, creating, and editing files; an exact recalculation command ('python scripts/recalc.py output.xlsx'); and the verbatim JSON output schema with field-by-field interpretation for acting on errors. It matches the 5 anchor ('copy-paste ready code or commands; specific examples cover the common cases') — the create/edit/analyze/recalculate cases are all covered with runnable code.

Workflow Clarity

The 'Common Workflow' section gives a numbered sequence with a mandatory validation step (step 5, recalc) and an explicit feedback loop (step 6: 'Fix the identified errors and recalculate again'), backed by a verification checklist and error-recovery guidance keyed to the script's JSON output. This matches the 5 anchor ('clear sequence with explicit validation steps; feedback loops for error recovery; checklists for complex processes'); the file-modifying batch workflow has its required validation loop, so no cap applies.

Progressive Disclosure

Section headers are present and the referenced bundle paths (scripts/recalc.py, scripts/office/soffice.py) are real and clearly signaled, but the ~290-line body keeps everything inline: the financial-model color/number-formatting standards and the repeated verification checklists are self-contained blocks that clearly belong in separate reference files, and the structure has gaps (a bare '## Excel File Workflows' heading with no content before the next H2, and a '## Recalculating formulas' section duplicating workflow step 5). This matches the 3 anchor ('some structure but could be better organized; content that should be separate is inline') better than 4, where organization gaps would be minor.

Specificity

The description lists multiple concrete actions — '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 convert between tabular file formats' — with comprehensive coverage across read/edit/create/convert scenarios. It sits at the 5 anchor ('multiple specific concrete actions; comprehensive coverage') rather than 4 because there are no minor gaps: each action category is enumerated with examples.

Completeness

It explicitly answers both 'what' (open/read/edit/fix, create, convert between tabular formats) and 'when' ('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 clearly matches the 5 anchor with concrete trigger phrases; it exceeds the 4 anchor, where the 'when' would be less explicit.

Trigger Term Quality

It covers natural terms and file extensions comprehensively: '.xlsx, .xlsm, .csv, or .tsv', 'spreadsheet file by name or path', a casual usage example ('"the xlsx in my downloads"'), and synonyms like 'messy tabular data files'. This matches the 5 anchor ('comprehensive coverage of natural terms including synonyms and file extensions'); a 4 would require natural terms to be missing, and none are.

Distinctiveness Conflict Risk

The niche is unambiguous — the deliverable must be a spreadsheet file — and an explicit exclusion list ('Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved') minimizes conflict with adjacent document/data skills. It fits the 5 anchor ('clear niche with distinct triggers; minimal conflict risk') rather than 4, which would allow minor overlap risk that the DO-NOT-trigger clause forecloses.