sales-data-extraction-agent
Monitors Excel spreadsheets (.xlsx/.xls) and extracts key sales metrics (MTD, YTD, Year End) to generate internal live reports. Use when the user needs to parse sales reports, track revenue figures, pull MTD/YTD data from a spreadsheet, build a sales dashboard, or automate extraction of sales performance data from Excel files into a database.
90
88%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Quality
Discovery
100%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a strong skill description that clearly defines its scope, uses concrete actions and specific terminology, and includes an explicit 'Use when...' clause with diverse trigger scenarios. It effectively combines domain specificity (sales metrics, MTD/YTD) with file format specificity (.xlsx/.xls) to create a distinctive and easily selectable skill. The description is concise yet comprehensive.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: monitors Excel spreadsheets, extracts key sales metrics (MTD, YTD, Year End), generates internal live reports. The description names specific file formats and metric types. | 3 / 3 |
Completeness | Clearly answers both 'what' (monitors Excel spreadsheets and extracts sales metrics to generate live reports) and 'when' (explicit 'Use when...' clause listing five distinct trigger scenarios including parsing sales reports, tracking revenue, pulling MTD/YTD data, building dashboards, and automating extraction). | 3 / 3 |
Trigger Term Quality | Excellent coverage of natural terms users would say: 'Excel', '.xlsx/.xls', 'sales metrics', 'MTD', 'YTD', 'sales reports', 'revenue figures', 'spreadsheet', 'sales dashboard', 'sales performance data'. These are terms users would naturally use when requesting this kind of work. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with a clear niche: the combination of Excel files + sales metrics + specific metric types (MTD/YTD/Year End) + live report generation creates a well-defined scope that is unlikely to conflict with generic spreadsheet or generic reporting skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
77%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a strong, highly actionable skill with executable code for every component and a well-structured workflow with explicit validation checkpoints and error recovery. Its main weakness is that it's quite long for a single SKILL.md file — the detailed implementation code for each subsystem would be better split into referenced files. The content is domain-specific and avoids explaining concepts Claude already knows, though some tightening is possible.
Suggestions
Split detailed implementation code (fuzzy mapping, row extraction, bulk insert) into separate referenced files (e.g., COLUMN_MAPPING.md, DB_OPERATIONS.md) and keep SKILL.md as a concise overview with the workflow diagram and critical rules.
Remove the duplicate embedded rubric/prompt text that appears to be a copy-paste artifact, which significantly inflates the document length.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is mostly efficient with domain-specific details Claude wouldn't know (alias lists, schema, fuzzy thresholds), but it's quite long. The repeated embedding of the full rubric/prompt text appears to be a copy-paste artifact that inflates the content. Some inline code blocks could be tightened, and the Excel input structure example table, while useful, is somewhat verbose. | 2 / 3 |
Actionability | The skill provides fully executable Python code for every component: file watching, fuzzy column mapping, metric detection, row extraction, SQL schema, and bulk insert with verification. All code is copy-paste ready with specific libraries, thresholds, and configurations. | 3 / 3 |
Workflow Clarity | The workflow section provides a clear numbered sequence with explicit validation checkpoints (row validation, post-insert count verification) and error recovery with rollback. The feedback loop for error recovery is well-documented, and the ASCII flow diagram makes the process unambiguous. | 3 / 3 |
Progressive Disclosure | The content has good section structure with numbered subsections, but it's monolithic — all detailed code is inline in a single file rather than being split into referenced files. For a skill this long (200+ lines of substantive content), the column alias lists, SQL schema, and individual component code would benefit from being in separate referenced files. | 2 / 3 |
Total | 10 / 12 Passed |
Validation
90%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 10 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 10 / 11 Passed | |
- Repository
- OpenRoster-ai/awesome-agents
- Commit
010799b
- Reviewed
Table of Contents
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