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db-extractor-sqlite

Extract SQLite database content to text-readable formats (CSV, JSON, Markdown) for LLM processing and content synthesis. Use when working with SQLite databases (.db, .sqlite, .sqlite3) from course materials, datasets, or applications that need to be converted to text formats for analysis, synthesis, or inclusion in LLM context windows. Routed from db-router skill.

Quality

87%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

The canonical home for this skill is db-extractor-sqlite in KennethJefferson/cc_sdk_knowledge_extractor

SKILL.md
Quality
Evals
Security

Quality

Content

80%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 body is lean, fully executable, and accurately documents the bundled script, but two rubric rules hold it back: the batch database-extraction workflow has no validation/verification checkpoint (capping workflow clarity at 3), and the provided references/format_guide.md is never linked from the body, leaving its detail undiscoverable. Both issues are cheap to fix and would lift the skill to top-tier quality.

Suggestions

Add a verification step after extraction (e.g., 'After running, confirm the output directory contains one file per expected table and spot-check row counts') so the batch database workflow has an explicit validation checkpoint.

Link references/format_guide.md from the Output Formats section (e.g., 'See [references/format_guide.md](references/format_guide.md) for token-optimization guidance and when to choose each format') instead of inlining a condensed duplicate with no pointer.

Consider noting the read-only nature of the script (it never modifies the source database) so Claude can reassure users about safety when extracting from production or course databases.

DimensionReasoningScore

Conciseness

The body is almost entirely executable commands, a compact format table, and a CLI reference — no explanations of concepts Claude already knows, no padded prose (comments like "(sqlite3 is built-in)" and "(keeps files manageable)" are one-line and useful). It matches 'lean and efficient; assumes Claude's competence; every token earns its place'.

5 / 5

Actionability

Every workflow is a copy-paste-ready command covering the common cases (default extraction, format choice, table selection/exclusion, row limits, schema docs), and the CLI Reference section matches the actual script's arguments (database, -o, -f, --tables, --exclude, --schema, --max-rows, -q). This matches the 'fully executable; copy-paste ready; covers common cases' anchor.

5 / 5

Workflow Clarity

The single-command invocation is unambiguous, but the skill is a batch database operation (extracts every table and writes many output files) with no validation or verification steps anywhere (e.g., checking output files exist or row counts after extraction). The rubric's cap for batch/database operations without validation limits this to 3, overruling the simple-skill exception; it is not 2 because the invocation and options are fully and coherently specified.

3 / 5

Progressive Disclosure

The body is well-sectioned and scripts/db_extract.py is thoroughly and correctly referenced, but references/format_guide.md is orphaned — never linked or mentioned anywhere in SKILL.md — so its format-comparison and token-optimization detail is undiscoverable, and a condensed version of it (the Output Formats table) is inlined without a pointer. This matches 'references present but not clearly signaled; content that should be separate is inline'; not 4 because the one provided reference file is completely unlinked rather than a minor signaling gap.

3 / 5

Total

16

/

20

Passed

Description

87%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.

A strong description: it explicitly states what the skill does and when to use it, with concrete trigger conditions, file extensions, and natural synonyms. The only minor gaps are unsaid capabilities (schema docs, table filtering) and a few missing colloquial trigger verbs like 'export' or 'dump'.

DimensionReasoningScore

Specificity

"Extract SQLite database content to text-readable formats (CSV, JSON, Markdown) for LLM processing and content synthesis" names the domain plus three concrete output formats and two purposes, matching the 'several specific actions; minor gaps' anchor. Not 3 (more than 1-2 generic actions via the enumerated formats), not 5 (it is one core extraction action with format variants; tool capabilities like --schema documentation and table filtering are unstated).

4 / 5

Completeness

The 'what' is explicit ("Extract SQLite database content to text-readable formats (CSV, JSON, Markdown)") and the 'when' is an explicit trigger clause ("Use when working with SQLite databases (.db, .sqlite, .sqlite3) from course materials, datasets, or applications that need to be converted... for analysis, synthesis, or inclusion in LLM context windows") with concrete trigger conditions. This matches the top anchor exactly; the trailing "Routed from db-router skill" adds routing context without weakening either part.

5 / 5

Trigger Term Quality

"SQLite databases (.db, .sqlite, .sqlite3)", "course materials, datasets, or applications", and "analysis, synthesis, or inclusion in LLM context windows" give good natural coverage including file extensions. Not 5 because common user phrasings like "export", "dump", or "convert my database" are absent, matching 'good keyword coverage; a few natural terms missing'.

4 / 5

Distinctiveness Conflict Risk

The description is scoped to SQLite with explicit file extensions and a clear niche (database-to-text conversion for LLM context), and "Routed from db-router skill" signals its place in a router family, giving minimal conflict risk with other skills. It fits the 'clear niche with distinct triggers' anchor.

5 / 5

Total

18

/

20

Passed

Validation

100%

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

KennethJefferson/mono-repo_db

Path

db-extractor-sqlite/SKILL.md

Reviewed

Table of Contents

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