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 agentmods add skills/orneryd/nornicdb/grpcnpx skills add orneryd/NornicDB --skill grpcgit clone --depth 1 https://github.com/orneryd/NornicDBWrote 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/orneryd/nornicdb/grpc)<a href="https://agentmods.dev/skills/orneryd/nornicdb/grpc"><img src="https://agentmods.dev/badge/skills/orneryd/nornicdb/grpc.svg" alt="Measured on agentmods" 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 | $0.00098 | $0.02293 |
| Opus 5 | $0.00049 | $0.01146 |
| Sonnet 5 | $0.00020 | $0.00459 |
| Haiku 4.5 | $0.00010 | $0.00229 |
Grade A, and why
nornicdb-grpc 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 yesterday.
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.
How it starts
The opening of the file, as written. The whole thing — 213 lines — stays where its author put it; the contents beside it link to each section on GitHub.
NornicDB gRPC (Qdrant + NornicSearch)
NornicDB exposes two gRPC services on the same listener:
- Qdrant compatibility — full set of
qdrant.Collections,qdrant.Points, andqdrant.Snapshotsservices. Existing Qdrant SDKs work without modification. NornicSearch— one additive RPC,SearchText, that returns hybrid (vector + BM25 + RRF) results.
The same client connection talks to both; pick whichever matches the operation.
Connection
| Setting | Value |
|---|---|
| Listen address | :6334 (NORNICDB_QDRANT_GRPC_LISTEN_ADDR) |
| Default port (host) | 6334 |
| Auth | Same Auth.Enabled flag as Bolt. When off, gRPC is open. When on, basic auth or bearer JWT in the gRPC metadata. |
| TLS | None by default (run behind a TLS proxy or in a private network). |
Enable the gRPC server (off by default):
export NORNICDB_QDRANT_GRPC_ENABLED=true
YAML:
features:
qdrant_grpc_enabled: true
qdrant_grpc_listen_addr: ":6334"
qdrant_grpc_max_vector_dim: 4096
qdrant_grpc_max_batch_points: 1000
qdrant_grpc_max_top_k: 1000
Limits (defaults)
| Limit | Default | Override |
|---|---|---|
| Max vector dimension | 4096 | NORNICDB_QDRANT_GRPC_MAX_VECTOR_DIM |
| Max points per Upsert batch | 1000 | NORNICDB_QDRANT_GRPC_MAX_BATCH_POINTS |
| Max top-K per Search | 1000 | NORNICDB_QDRANT_GRPC_MAX_TOP_K |
| Max payload bytes per point | 1 MB | (not configurable) |
| Max filter clauses per request | 100 | (not configurable) |
| Request timeout | 30 s | (not configurable) |
| Max gRPC message size (recv/send) | 64 MB | (not configurable) |
Data model mapping
| Qdrant concept | NornicDB equivalent | Storage detail |
|---|---|---|
| Collection | Database (namespace) | DatabaseManager.GetStorage(collectionName); all point keys live under collectionName: |
| Point | Node | Node ID is qdrant:point:<rawID>. Labels include QdrantPoint, Point. |
| Point payload | node.Properties |
Internal _qdrant_* keys are stripped from outbound responses. |
| Single vector | node.NamedEmbeddings["default"] |
|
| Named vectors | node.NamedEmbeddings[<vectorName>] |
Each named vector is independently searchable. |
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.
- yesterday First seen · 213 lines · 98 tokens per session scan A ca9ab7e20ca2
nornicdb-grpc is a skill published in the GitHub repository orneryd/NornicDB (858 stars, last pushed yesterday), licensed MIT. It adds 98 tokens to every session and 2,293 once invoked, about $0.0005 per session on Opus 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 2026-09-05.
Other skills, from other repositories
payload
Use when working with Payload projects (payload.config.ts, collections, fields, hooks, access control, Payload API). Use when debugging validation errors, security issues, relationship queries, transactions, or hook behavior.
pydantic-resolve-3step
基于 pydantic-resolve 的三阶段开发模式，用于构建从建模讨论到生产部署的完整项目。适用于需要使用 ER Diagram + ORM + DefineSubset 渐进式开发的场景。.
webiny-api-opensearch-catalog
Name: createOpenSearchClient Import: import { createOpenSearchClient } from "webiny/api/opensearch" Source: @webiny/api-opensearch/client.ts.
fabric-app-sqldb-writeback
Use when a Fabric App needs transactional WRITE-BACK (comments, edits, requests, approvals) on top of Lakehouse data — 'users edit data in my Fabric app', 'write back to the source', 'my saved comment takes forever to appear', 'read-your-own-writes', 'mirror Gold into the app database', 'seed the Rayfin SQL DB…
hasura-graphql-engine
Complete guide for Hasura GraphQL Engine including instant GraphQL APIs, permissions, authentication, event triggers, actions, and production deployment.
event-store-design
Design and implement event stores for event-sourced systems. Use when building event sourcing infrastructure, choosing event store technologies, or implementing event persistence patterns.