Conciseness

The body is a mostly lean CLI reference with concrete commands and no explanation of concepts Claude already knows, but includes minor trimmable content such as the restated opening sentence, the pip-install dependency section, and the 'Single format outputs files directly...' note. It fits anchor 4 (efficient with minor over-explanation) rather than 5, since a few tokens do not earn their place, and rather than 3, since there is no genuinely padded or unnecessary explanation.

Actionability

All examples are fully executable copy-paste commands ('python scripts/db_extract.py mysql://user:password@localhost:3306/mydb', '--tables users,posts,comments', '--max-rows 50') covering the common cases, and the documented CLI Reference matches the actual script's argparse options exactly. This matches anchor 5; it is above anchor 4 because there are no gaps in the concrete guidance.

Workflow Clarity

The single action (run the extractor with options) is unambiguous and sections are organized by workflow, but this is a batch database operation (default extracts every table) with no validation or verification step in the body — no output check, row-count sanity check, or error-recovery loop. Per the rubric's cap, batch/database operations without validation cannot score above 3, which overrides the simple-skill exception.

Progressive Disclosure

The body is well structured (Quick Start, workflows, CLI Reference) and references a real script, but the bundle's references/mysql_guide.md is never mentioned anywhere in the body, leaving its troubleshooting, format-selection, and token-optimization content orphaned and undiscoverable. It also duplicates the guide's Connection String Format section inline; this matches anchor 3 (references present but not clearly signaled, content that should be separate is inline) rather than 4, because a provided reference file is completely invisible rather than just imperfectly signaled.

Specificity

'Extract MySQL database content to text-readable formats (CSV, JSON, Markdown)' names the domain and one core action with enumerated output formats; the listed purposes ('analysis, synthesis, or inclusion in LLM context windows') are use cases, not additional actions. This matches anchor 3 (domain plus 1-2 concrete actions) rather than 4, whose example lists several distinct operations such as extracting, filling forms, and converting pages.

Completeness

It explicitly answers both questions: the 'what' is 'Extract MySQL database content to text-readable formats (CSV, JSON, Markdown) for LLM processing and content synthesis' and the 'when' is 'Use when working with MySQL databases that need to be converted to text formats for analysis, synthesis, or inclusion in LLM context windows'. The trigger guidance is explicit and specific with concrete contexts, matching anchor 5 rather than 4, where the 'when' would be less explicit.

Trigger Term Quality

Natural terms users would say are well covered: 'MySQL', 'database', 'extract', 'CSV', 'JSON', 'Markdown', 'LLM context windows'. It falls short of anchor 5 because common synonyms and variations like 'export', 'dump', or 'SQL' are missing, fitting anchor 4 (good keyword coverage, a few natural terms missing).

Distinctiveness Conflict Risk

The description carves a clear niche (MySQL-to-text extraction) and even notes 'Routed from db-router skill' to disambiguate routing; it would not naturally trigger for non-MySQL or non-extraction tasks. This matches anchor 5 (clear niche with distinct triggers, minimal conflict risk) rather than 4, which allows overlap with closely related skills.