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 Galbaz1/video-research-mcp --skill mlflow-tracesgit clone --depth 1 https://github.com/Galbaz1/video-research-mcpWrote 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/galbaz1/video-research-mcp/mlflow-traces)<a href="https://agentmods.dev/skills/galbaz1/video-research-mcp/mlflow-traces"><img src="https://agentmods.dev/badge/skills/galbaz1/video-research-mcp/mlflow-traces/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/galbaz1/video-research-mcp/mlflow-traces"><img src="https://agentmods.dev/badge/skills/galbaz1/video-research-mcp/mlflow-traces.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 | $0.00037 | $0.01698 |
| Opus 5.5 | $0.00015 | $0.00679 |
| Sonnet 5.5 | $0.00007 | $0.00340 |
| Haiku 4.5 | $0.00004 | $0.00170 |
Grade A, and why
mlflow-traces 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 20d 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.
How it starts
The opening of the file, as written. The whole thing — 169 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MLflow Trace Management — video-research-mcp
Overview
Query, tag, evaluate, and manage MLflow traces captured from video-research-mcp Gemini API calls. Uses mcp__mlflow-mcp__* MCP tools — no code writing needed for most operations.
Core principle: Search first, then act. Always verify before destructive operations.
Quick Reference
| Task | Tool | Key Params |
|---|---|---|
| Find traces | search_traces |
experiment_id, filter_string, extract_fields |
| Get details | get_trace |
trace_id, extract_fields |
| Tag trace | set_trace_tag |
trace_id, key, value |
| Log score | log_feedback |
trace_id, name, value, rationale |
| Run scorers | evaluate_traces |
experiment_id, trace_ids, scorers |
| List scorers | list_scorers |
— |
Canonical Field Paths
CRITICAL — only use fields that actually exist:
| Path | Content | Common mistake |
|---|---|---|
info.trace_id |
Trace identifier | — |
info.state |
Status: OK, ERROR | NOT info.status |
info.request_time |
Timestamp | NOT info.timestamp_ms |
info.execution_duration_ms |
Duration in ms | NOT info.execution_duration |
info.request_preview |
First ~100 chars of request | — |
info.response_preview |
First ~100 chars of response | — |
info.tags |
All tags as object | Use info.tags.* for all |
data.spans.*.name |
Span names | Must include data. prefix |
data.spans.*.status_code |
Span status | NOT data.spans.*.status |
data.spans.*.inputs |
Span inputs | Moderate size |
data.spans.*.outputs |
Span outputs | Moderate size |
extract_fields Discipline
Always use extract_fields. Video-research-mcp traces contain video URIs, cached content references, full Gemini prompts/responses. A single get_trace without extract_fields can flood your context window.
// BAD - pulls everything
get_trace({ trace_id: "tr-..." })
search_traces({ experiment_id: "2" })
// GOOD - selective fields
get_trace({ trace_id: "tr-...",
extract_fields: "info.*,data.spans.*.name,data.spans.*.status_code" })
search_traces({ experiment_id: "2", max_results: 10,
extract_fields: "info.trace_id,info.state,info.execution_duration_ms" })
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.
- 20d ago Changed e7f8aa5d6c23
- 1mo ago First seen · 169 lines · 37 tokens per session scan A f68ebe463b56
mlflow-traces is a skill published in the GitHub repository Galbaz1/video-research-mcp (23 stars, last pushed 3d ago), licensed MIT. It adds 37 tokens to every session and 1,698 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.
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