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/dinglebear-ai/dendrite/qdrantnpx skills add dinglebear-ai/dendrite --skill qdrantgit clone --depth 1 https://github.com/dinglebear-ai/dendriteWrote 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/dinglebear-ai/dendrite/qdrant)<a href="https://agentmods.dev/skills/dinglebear-ai/dendrite/qdrant"><img src="https://agentmods.dev/badge/skills/dinglebear-ai/dendrite/qdrant.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 | $0.00085 | $0.01098 |
| Opus 5 | $0.00043 | $0.00549 |
| Sonnet 5 | $0.00017 | $0.00220 |
| Haiku 4.5 | $0.00009 | $0.00110 |
Grade B, and why
qdrant scanned grade B with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Sends data to an external URLmediumData exfiltration
A POST to an outside endpoint may be telemetry or may be exfiltration; either way the mod talks to somewhere, and you should know where.
| Create collection | `curl -sS -X PUT "${AUTH[@]}" -H 'Content-Type: application/json' "$QDRANT_URL/collections/<name>" -d '{"vectors":{"size":<dim>,"distance":"Cosine"}}'` | Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
| Server health / version | `curl -sS "${AUTH[@]}" "$QDRANT_URL/"` | The source is not reproduced here
Licensed AGPL-3.0
The repository is licensed AGPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
What ships with it
4 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.
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.
- 3d ago First seen · 83 lines · 85 tokens per session scan B 61420193cd21
qdrant is a skill published in the GitHub repository dinglebear-ai/dendrite (1 stars, last pushed 7d ago), licensed AGPL-3.0. It adds 85 tokens to every session and 1,098 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it B with 2 findings (sends data to an external url, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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