What is sqlite-vectordb?

A SQLite-based store for work logs with vector search, which finds related notes by meaning rather than only matching exact words.

It adds work-log entries, searches them by topic or tags, filters results, and removes outdated or incorrect entries.

It keeps past work searchable so useful context is easier to recover and duplicate effort is less likely.

How syi0808/screenize configures Claude Code

Reuse

Borrowing it

Nothing to install: this file belongs to syi0808/screenize. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/syi0808/screenize/main/.claude/skills/sqlite-vectordb/SKILL.md

Clone the repo

git clone --depth 1 https://github.com/syi0808/screenize

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/syi0808/screenize/sqlite-vectordb/github.svg)](https://agentmods.dev/skills/syi0808/screenize/sqlite-vectordb)

Your own site

<a href="https://agentmods.dev/skills/syi0808/screenize/sqlite-vectordb"><img src="https://agentmods.dev/badge/skills/syi0808/screenize/sqlite-vectordb/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/syi0808/screenize/sqlite-vectordb"><img src="https://agentmods.dev/badge/skills/syi0808/screenize/sqlite-vectordb.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 33 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 969 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector pass 7 Sept 2026

How audits are shown

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00033	$0.00969
Opus 5.5	$0.00013	$0.00388
Sonnet 5.5	$0.00007	$0.00194
Haiku 4.5	$0.00003	$0.00097

Measured 2mo ago against content hash c43f632de582, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

sqlite-vectordb scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.

The scan reads SKILL.md. This mod also ships 6 executable files (scripts/add_entry.py, scripts/config.py, scripts/delete_entry.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.claude/skills/sqlite-vectordb/SKILL.md · 135 lines

How it starts

The opening of the file, as written. The whole thing — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.

SQLITE VECTOR DB SKILL

Store work logs in a searchable vector database and provide semantic search infrastructure.

When to use:

Add entry: After /log-work execution (integrated with work-logger)
Search: When previous work context is needed (called by work-context-finder)
Delete: To clean up incorrect/outdated logs

Note: DB initializes automatically. No need to run init_db.py manually.

Add Entry

Index a markdown log into the vector DB.

uv run .claude/skills/sqlite-vectordb/scripts/add_entry.py \
  --file "private-docs/work-logs/YYYY-MM-DD-slug.md" \
  --summary "One-line summary" \
  --tags "tag1,tag2"

--file, -f (required): Work log file path
--summary, -s (required): One-line summary for search indexing
--tags, -t (required): Comma-separated tags

Search

Semantic similarity search in work logs.

uv run .claude/skills/sqlite-vectordb/scripts/search.py \
  --query "search terms" \
  --limit 5

--query, -q (required): Search query
--limit, -l: Max results (default: 5)
--tag, -t: Filter by tag
--type, -T: Filter by log type
--json, -j: JSON output

Delete Entry

Remove a work log entry from the database.

uv run .claude/skills/sqlite-vectordb/scripts/delete_entry.py \
  --file "private-docs/work-logs/YYYY-MM-DD-slug.md"

Initialize DB (Optional)

Manual schema creation. Usually not needed - other scripts auto-initialize.

uv run .claude/skills/sqlite-vectordb/scripts/init_db.py

<technical_specs>

DB location: private-docs/work-logs/.vector-db/work-logs.db
Engine: SQLite + sqlite-vec extension
Embedding model: all-MiniLM-L6-v2 (384-dim)
Chunk types: summary, details, challenges, other
Execution: uv run with PEP 723 inline deps
Schema reference: references/schema.md

</technical_specs>

Language requirement: All data stored in the vector DB MUST be written in English.

Read the full file on GitHub · 135 lines

Files

What ships with it

8 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

2mo ago First seen · 135 lines · 33 tokens per session scan A c43f632de582

Subscribe to this mod's changes

sqlite-vectordb is a skill published in the GitHub repository syi0808/screenize (619 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 33 tokens to every session and 969 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Data and AI Memory and context RAG and vectors

sqlite-vectordb next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
sqlite-vectordbsyi0808/screenize	Skill	619	5mo ago	Apache-2.0	A	33	Claude Code
AgentDB Memory Patternsruvnet/RuView	Skill	103k	yesterday	MIT	A	45	Claude Code
agent-v3-memory-specialistruvnet/ruflo	Skill	81k	yesterday	MIT	A	25	Claude Code
agents-langchaindavila7/claude-code-templates	Skill	33k	yesterday	MIT	A	80	Claude Code, Codex
knowledge-orgbojieli/ai-agent-book	Skill	57k	29d ago	Apache-2.0	A	96	Claude Code, Codex
xerjxerj-org/xerj	Skill	19k	today	Apache-2.0	A	38	Claude Code, Codex
llm-wikiAr9av/obsidian-wiki	Skill	3.7k	yesterday	MIT	A	41	Claude Code

screenize: Skill for Claude Code