Conciseness

The body is lean and assumes competence (no MySQL tutorials, no library explanations), but has trimmable redundancy: connection-string examples appear in both "Quick Start" and "Connection String Format", and the opening line restates the frontmatter description. Anchor 5 would require every token to earn its place.

Actionability

Every example is copy-paste executable against the real scripts/db_extract.py, the Quick Start covers the common cases (default CSV, JSON, markdown, all+schema), and the CLI reference lists every flag with defaults. Specific workflows cover selective extraction and large-database handling.

Workflow Clarity

The single-command sequence is unambiguous, but this is a database batch operation and the body contains no validation or verification steps (no output check, no error-recovery guidance — troubleshooting lives only in the unreferenced guide). Per the rubric cap, database/batch workflows without feedback loops cannot score above 3; it is not lower because the sequence itself is clear.

Progressive Disclosure

Inline structure is good (clear sections, appropriately sized), and scripts/db_extract.py is consistently referenced. However references/mysql_guide.md — which contains troubleshooting, token optimization, and password special-character handling that complements the body — is never mentioned, so it is undiscoverable and its connection-format content is partially duplicated inline. Anchor 4 requires references to be mostly clearly signaled, which this misses.

Specificity

"Extract MySQL database content to text-readable formats (CSV, JSON, Markdown) for LLM processing and content synthesis" names the domain and concrete actions with three explicit output formats and purposes. It stops short of anchor 5 because the action set is essentially one extract-and-convert operation rather than multiple distinct capabilities.

Completeness

Both parts are explicit: what — "Extract MySQL database content to text-readable formats (CSV, JSON, Markdown) for LLM processing and content synthesis"; when — "Use when working with MySQL databases that need to be converted to text formats for analysis, synthesis, or inclusion in LLM context windows", with three concrete trigger contexts. Anchor 4 would require the 'when' to be less explicit than it is.

Trigger Term Quality

Natural terms present: "MySQL", "database", "CSV", "JSON", "Markdown", "LLM", "converted to text formats", "analysis, synthesis". A few common synonyms users would say are missing ("export", "dump", "SQL"), so it does not reach anchor 5's comprehensive synonym/extension coverage.

Distinctiveness Conflict Risk

"MySQL database" is a clear niche with distinct triggers, and "Routed from db-router skill" clarifies its place in a router family without introducing overlap. Minimal conflict risk with non-MySQL or non-database skills.