TruLens is an open-source system for tracing and evaluating LLM applications and AI agents. It records each step's inputs, outputs, latency, tokens, and cost, then uses evaluations to find failures and compare application versions.
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 truera/trulens --skill qdrant-search-qualitygit clone --depth 1 https://github.com/truera/trulensWrote 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/truera/trulens/qdrant-search-quality)<a href="https://agentmods.dev/skills/truera/trulens/qdrant-search-quality"><img src="https://agentmods.dev/badge/skills/truera/trulens/qdrant-search-quality/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/truera/trulens/qdrant-search-quality"><img src="https://agentmods.dev/badge/skills/truera/trulens/qdrant-search-quality.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 | $0.00144 | $0.00550 |
| Opus 5.5 | $0.00058 | $0.00220 |
| Sonnet 5.5 | $0.00029 | $0.00110 |
| Haiku 4.5 | $0.00014 | $0.00055 |
Grade A, and why
qdrant-search-quality 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 22d 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
Qdrant Search Quality
Route first, then answer. Match the user's symptom in the table, Read that file, and answer from it.
Do not answer from this page alone: it contains routing only, not the guidance. If two rows match, read both.
| The user says | Read |
|---|---|
| Search results are bad or irrelevant, wrong results, missing expected matches | diagnosis/SKILL.md |
| Low recall, expected results are missing | diagnosis/SKILL.md |
| Low precision, too many wrong matches | diagnosis/SKILL.md |
| Which embedding model to use, quality dropped after quantization, model change, or data growth | diagnosis/SKILL.md |
| Not sure if the model, the data, or Qdrant is at fault | diagnosis/SKILL.md |
| Want to measure recall, build a golden set, ground truth dataset, recall@k | diagnosis/SKILL.md |
| Need to combine keyword and semantic search, hybrid search, sparse + dense, fusion / RRF, prefetch | search-strategies/hybrid-search/SKILL.md |
| Should I rerank, results too similar, need diversity, MMR, recommendation/discovery API | search-strategies/SKILL.md |
| Improving results with relevance feedback or user clicks, cheaper alternative to reranking | search-strategies/relevance-feedback/SKILL.md |
Most quality issues come from the embedding model or the data, not from Qdrant's configuration — splitting chunks mid-sentence alone can drop quality 30-40%. Rule that out with exact search before tuning any Qdrant parameter: Search API
What ships with it
6 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.
- 22d ago First seen · 30 lines · 144 tokens per session scan A b61d530c13f3
qdrant-search-quality is a skill published in the GitHub repository truera/trulens (3,602 stars, last pushed today), licensed MIT. It adds 144 tokens to every session and 550 once invoked, about $0.0006 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 2026-09-24.
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