incremental-excel-build

Build complex Excel files through staged, verifiable steps with intermediate CSV outputs for debugging

Quality

68%

Does it follow best practices?

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Securityby

Passed

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tessl review fix ./benchmarks/gdpval/skills/incremental-excel-build/SKILL.md

Quality

Content

77%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The content is highly actionable with clear sequencing and per-stage verification checkpoints, but it is somewhat verbose due to repeated script boilerplate and inlines all code rather than offloading scripts to a bundle.

Suggestions

Move the four stage scripts and runner into a scripts/ bundle and reference them, keeping only key excerpts and the workflow inline in SKILL.md.

Trim obvious inline comments (e.g., '# Handle missing values', '# Filter active stores') that restate basic pandas operations Claude already knows.

Factor the repeated import and __main__ boilerplate out of the inlined examples to reduce token overhead.

Dimension	Reasoning	Score
Conciseness	The body is mostly efficient code with brief prose, but repeated boilerplate (imports, __main__ guards) across four scripts and obvious comments explaining basic pandas operations could be tightened.	3 / 5
Actionability	All four stage scripts and the runner are fully executable, copy-paste-ready Python with complete imports, functions, and an orchestrator covering the common pipeline case.	5 / 5
Workflow Clarity	The four stages are clearly sequenced with an explicit 'Verification checkpoint' after each, plus a runner with error detection and early exit, giving a clear feedback loop for this batch operation.	5 / 5
Progressive Disclosure	Sections are well organized, but all four full scripts are inlined in SKILL.md with no bundle files or external references, so content that could live in a scripts/ bundle is not split out.	3 / 5
	Total	16 / 20 Passed

Description

58%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description clearly states what the skill does and is reasonably specific and distinctive, but it omits explicit trigger guidance (a "Use when..." clause) and lacks keyword synonyms like spreadsheets or .xlsx.

Suggestions

Add an explicit 'Use when...' clause naming trigger scenarios (e.g., building Excel files with calculations, forecasts, or multi-stage transformations).

Include keyword synonyms users naturally say, such as 'spreadsheets', 'workbook', '.xlsx', or 'tabular data'.

Optionally mention the deliverable form (formatted .xlsx output) to broaden specificity.

Dimension	Reasoning	Score
Specificity	Lists several concrete actions ("Build complex Excel files", "staged, verifiable steps", "intermediate CSV outputs for debugging") with only minor coverage gaps such as styling or charts.	4 / 5
Completeness	The "what" is clear (staged Excel builds with CSV intermediates) but there is no "Use when..." clause, so the trigger guidance is missing and capped at 3.	3 / 5
Trigger Term Quality	"Excel files" is a relevant keyword but common synonyms users would say (spreadsheets, .xlsx, workbook, tabular data) are missing.	3 / 5
Distinctiveness Conflict Risk	The staged-build-with-CSV-checkpoints niche is mostly distinct from generic Excel skills, with only minor overlap risk against general spreadsheet helpers.	4 / 5
	Total	14 / 20 Passed

Validation

100%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: HKUDS/OpenSpace
Path: benchmarks/gdpval/skills/incremental-excel-build/SKILL.md
Commit: 3827781

Reviewed: 13 days ago

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