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 5.5 | $0.00034 | $0.00288 |
| Sonnet 5.5 | $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 2mo 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.
- 2mo 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 6mo ago), licensed MIT. It adds 86 tokens to every session and 719 once invoked, about $0.0003 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 2026-08-31.
Other agents, from other repositories
code-refactoring-legacy-modernizer
Refactor legacy codebases, migrate outdated frameworks, and implement gradual modernization. Handles technical debt, dependency updates, and backward compatibility. Use PROACTIVELY for legacy system updates, framework migrations, or technical debt reduction.
architect
Deep reasoning agent. Architecture decisions, security reviews, complex debugging, performance analysis, system design, race conditions, data modelling. Use when getting it wrong has high cost.
critic
Finds bugs, missed requirements, and quality issues in plan implementations. Spawned after all tasks pass review for a final sweep.
kingdee-qa-engineer
QA & Test Engineer for the kingdee-mcp project. Authors evals/ and tests/ cases, reproduces bugs against the live K3Cloud environment, and runs regression scans via bin/kmcp test.
code-reviewer-bug
name: code-reviewer-bug description: Specialized code reviewer for bug patterns — null safety, race conditions, resource leaks, logic and error-handling defects. Returns scored findings (severity × impact × confidence). skills: code-review model: inherit.
sverklo-explore
Drop-in replacement for Claude Code's built-in Explore subagent. Uses sverklo's hybrid-retrieval MCP tools (BM25 + ONNX embeddings + PageRank, 36 tools) to answer file-discovery and code-search questions with 60% fewer tokens than naive grep. Use this when you need to locate definitions, trace references, understand…