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 Ansumanbhujabal/Polly_Harness --skill langfusegit clone --depth 1 https://github.com/Ansumanbhujabal/Polly_HarnessWrote 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/ansumanbhujabal/polly_harness/langfuse)<a href="https://agentmods.dev/skills/ansumanbhujabal/polly_harness/langfuse"><img src="https://agentmods.dev/badge/skills/ansumanbhujabal/polly_harness/langfuse/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/ansumanbhujabal/polly_harness/langfuse"><img src="https://agentmods.dev/badge/skills/ansumanbhujabal/polly_harness/langfuse.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 | $0.00100 | $0.01633 |
| Opus 5.5 | $0.00040 | $0.00653 |
| Sonnet 5.5 | $0.00020 | $0.00327 |
| Haiku 4.5 | $0.00010 | $0.00163 |
Grade A, and why
langfuse scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- Bash(curl *langfuse.com/*) This is a copy
100% identical to langfuse — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Langfuse
This skill helps you use Langfuse effectively across all common workflows: instrumenting applications, migrating prompts, debugging traces, and accessing data programmatically.
Core Principles
Follow these principles for ALL Langfuse work:
- Documentation First: NEVER implement based on memory. Always fetch current docs before writing code (Langfuse updates frequently) See the section below on how to access documentation.
- CLI for Data Access: Use
langfuse-cliwhen querying/modifying Langfuse data. See the section below on how to use the CLI. - Best Practices by Use Case: Check the relevant reference file below for use-case-specific guidelines before implementing
- Use latest Langfuse versions: Unless the user specified otherwise or there's a good reason, always use the latest version of Langfuse SDKs/APIs.
Use case specific references
- instrumenting an existing function/application: references/instrumentation.md
- migrating prompts from a codebase into Langfuse: references/prompt-migration.md
- capturing user feedback (thumbs, ratings, implicit signals) as scores on traces: references/user-feedback.md
- further tips on using the Langfuse CLI: references/cli.md
- upgrading or migrating Langfuse SDKs to the latest version: references/sdk-upgrade.md
- judge calibration (LLM-as-a-Judge reliability, simple accuracy checks, advanced split-based validation, confusion matrices, and metric ingestion): references/judge-calibration.md
- systematic error analysis — reading traces, building failure taxonomy, deciding what to fix: references/error-analysis.md
- setting up CI/CD experiment gates with
langfuse/experiment-action: references/ci-cd.md - submitting feedback about this skill: references/skill-feedback.md
1. Langfuse API via CLI
Use the langfuse-cli to interact with the full Langfuse REST API from the command line. Run via npx (no install required):
Start by discovering the schema and available arguments:
# Discover all available resources
npx langfuse-cli api __schema
# List actions for a resource
npx langfuse-cli api <resource> --help
# Show args/options for a specific action
npx langfuse-cli api <resource> <action> --help
What ships with it
9 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.
- references/ci-cd.md 2.9 KB
- references/cli.md 1.9 KB
- references/error-analysis.md 4.5 KB
- references/instrumentation.md 8.7 KB
- references/judge-calibration.md 11 KB
- references/prompt-migration.md 7.6 KB
- references/sdk-upgrade.md 7.7 KB
- references/skill-feedback.md 2.3 KB
- references/user-feedback.md 4.3 KB
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 · 144 lines · 100 tokens per session scan A 3de7bf61480e
langfuse is a skill published in the GitHub repository Ansumanbhujabal/Polly_Harness (2 stars, last pushed 4mo ago), licensed MIT. It adds 100 tokens to every session and 1,633 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). It is 100% identical to langfuse, differing in 0 lines, and is treated as a copy.
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