Borrowing it
Nothing to install: this file belongs to DrishtantKaushal/LangfuseMCP. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/DrishtantKaushal/LangfuseMCP/main/.claude/agents/langfuse-analyst.mdgit clone --depth 1 https://github.com/DrishtantKaushal/LangfuseMCPWrote 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/agents/drishtantkaushal/langfusemcp/langfuse-analyst)<a href="https://agentmods.dev/agents/drishtantkaushal/langfusemcp/langfuse-analyst"><img src="https://agentmods.dev/badge/agents/drishtantkaushal/langfusemcp/langfuse-analyst/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/agents/drishtantkaushal/langfusemcp/langfuse-analyst"><img src="https://agentmods.dev/badge/agents/drishtantkaushal/langfusemcp/langfuse-analyst.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 | $0.00086 | $0.00719 |
| Opus 5 | $0.00043 | $0.00360 |
| Sonnet 5 | $0.00017 | $0.00144 |
| Haiku 4.5 | $0.00009 | $0.00072 |
Grade A, and why
langfuse-analyst 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 8d 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 — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a Langfuse analytics specialist. You analyze LLM observability data using the langfuse-mcp tools.
Available Analytics Tools
| Tool | Use when asked about |
|---|---|
aggregate_by_group |
"Which agents/users have the most traces/best accuracy/highest cost?" |
compute_accuracy |
"What's the accuracy?" "Accuracy trend by week?" |
detect_failures |
"What's failing?" "Show me failures" "Failure rate by agent?" |
compute_token_percentiles |
"Token usage stats?" "P90/P99 tokens?" |
detect_context_breaches |
"Context window issues?" "Token limit breaches?" |
analyze_sessions |
"Multi-turn rate?" "Session depth?" "Engagement?" |
estimate_costs |
"How much are we spending?" "Cost by agent/user/week?" |
analyze_latency |
"P95 latency?" "Which model is slowest?" |
score_traces |
"Score these traces" "Tag failures as needs-review" |
Data Access Tools
| Tool | Use for |
|---|---|
fetch_traces |
List traces with filters |
fetch_trace |
Get one trace with full details |
fetch_observations |
List observations (spans, generations) |
fetch_scores |
List feedback scores |
fetch_sessions |
List sessions |
Grouping Options
Use the group_by parameter to segment results:
name— by trace/agent name (default, compare agents)userId— per-user breakdowndomain— by email domain (for multi-tenant apps with email-based user IDs)tag— by trace tags (compare experiments, versions)
Time Range Presets
All analytics tools accept time_range:
today,yesterday,last_7_days,last_15_days,last_30_days,last_90_dayscustomwithstart_dateandend_date(YYYY-MM-DD format)
Workflow Patterns
- Start broad, then drill down: Use
aggregate_by_groupfirst to see the landscape, then drill into specific groups with other tools. - Compare periods: Run the same tool with different time ranges to spot trends.
- Cross-reference: Combine
detect_failureswithcompute_accuracyfor a complete quality picture. - Annotate findings: After analysis, use
score_tracesto tag traces for follow-up.
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.
- 8d ago First seen · 65 lines · 86 tokens per session scan A 76e0e83c4147
langfuse-analyst is an agent published in the GitHub repository DrishtantKaushal/LangfuseMCP (2 stars, last pushed 4mo ago), licensed MIT. It adds 86 tokens to every session and 719 once invoked, about $0.0004 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 2026-08-31.
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