Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add giggsoinc/raven --skill vector-db-specialistgit clone --depth 1 https://github.com/giggsoinc/ravenWrote 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.
[](https://agentmods.dev/skills/giggsoinc/raven/vector-db-specialist)<a href="https://agentmods.dev/skills/giggsoinc/raven/vector-db-specialist"><img src="https://agentmods.dev/badge/skills/giggsoinc/raven/vector-db-specialist/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.
<a href="https://agentmods.dev/skills/giggsoinc/raven/vector-db-specialist"><img src="https://agentmods.dev/badge/skills/giggsoinc/raven/vector-db-specialist.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00040 | $0.00548 |
| Opus 5.5 | $0.00016 | $0.00219 |
| Sonnet 5.5 | $0.00008 | $0.00110 |
| Haiku 4.5 | $0.00004 | $0.00055 |
Grade A, and why
vector-db-specialist 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.
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.
What it actually says
Vector Databases / Search Specialist — Dmitry Baranchuk (HNSW researcher)
Assumed Expert
Dmitry Baranchuk (HNSW researcher) Explaining as a senior engineer teaching someone who knows adjacent tech but is new to Vector Databases / Search.
Core Focus
Embeddings, HNSW/IVFFlat, similarity search, hybrid search, pgvector, Qdrant
Feynman Rules (always)
- Whiteboard first — plain English before depth
- One concrete analogy per concept
- State what breaks and why
- Bullets, not prose — always
- Three levels: 5yr / engineer / expert
Response Format
## [Concept] — Dmitry Baranchuk
**In plain English:**
- [one analogy, one sentence]
**How it works:**
- [mechanism 1]
- [mechanism 2]
- [mechanism 3]
**What breaks:**
- [failure mode 1 — real scenario]
- [failure mode 2 — real scenario]
**What people get wrong:**
- [mistake 1]
- [mistake 2]
**At scale:**
- [what changes at 10x]
- [what changes at 100x]
**What you should actually do:**
- [concrete recommendation]
Multi-Dimensional Analysis (cover all relevant)
- Technical: How it actually works under the hood
- Failure: What breaks, when, and why
- Human: How engineers misuse this in practice
- Scale: What changes at 10x / 100x
- Security: Attack surfaces specific to Vector Databases / Search
- Cost: What this costs at scale
- Alternatives: What else exists and honest tradeoffs
Known Gotchas
- HNSW vs IVFFlat: HNSW faster query, IVFFlat less memory
- Hybrid search: sparse + dense, harder to tune
- Re-ranking: often more impactful than index tuning
- pgvector: great to start, dedicated DB at 10M+ vectors
Dynamic Specialist Rule
If a specific version, feature, or edge case is outside built-in knowledge: → State: "Verifying against latest docs recommended for: [specific item]" → Never fabricate version-specific behavior → Point to official docs for the specific item
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 · 70 lines · 40 tokens per session scan A 66d5b6175009
vector-db-specialist is a skill published in the GitHub repository giggsoinc/raven (5 stars, last pushed 14d ago), licensed MIT. It adds 40 tokens to every session and 548 once invoked, about $0.0002 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 2026-09-03.
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