langfuse-deploy-integration

Deploy Langfuse with your application across different platforms. Use when deploying Langfuse to Vercel, AWS, GCP, or Docker, or integrating Langfuse into your deployment pipeline. Trigger with phrases like "deploy langfuse", "langfuse Vercel", "langfuse AWS", "langfuse Docker", "langfuse production deploy".

Quality

82%

Does it follow best practices?

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Securityby

Passed

No findings from the security scan

Quality

Content

82%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A highly actionable, well-structured deployment skill with copy-paste recipes for each platform and useful cross-cutting tables. Main gaps are missing post-deploy verification on some platforms and no use of bundle files to split the sizable inline content.

Suggestions

Add an explicit post-deploy verification step (e.g., checking traces appear in Langfuse, or hitting the health endpoint) to the Vercel, Lambda, and Cloud Run sections to reach a full validation feedback loop.

Consider moving the large per-platform code recipes into reference files under ./references/ (e.g., vercel.md, lambda.md) and keeping SKILL.md as a concise overview with one-level-deep links, which would improve progressive disclosure.

Trim a few redundant code comments and the prose in the Serverless note to push conciseness toward fully lean.

Dimension	Reasoning	Score
Conciseness	The body is code-first and lean with minimal padding and no over-explanation of basic concepts; a few explanatory notes and code comments could be trimmed slightly, keeping it just below a 5.	4 / 5
Actionability	Provides fully executable, copy-paste-ready code and commands for each platform (TypeScript handlers, docker-compose.yml, gcloud and vercel CLI commands) covering the common deployment cases.	5 / 5
Workflow Clarity	Steps 1-5 are clearly sequenced with a validation checkpoint in the Docker step (healthcheck + curl verify) and a dedicated health-check section plus error-handling table, but Vercel/Lambda/Cloud Run steps lack explicit post-deploy verification.	4 / 5
Progressive Disclosure	Content is well-organized into clear sections (Overview, Prerequisites, per-platform Instructions, considerations, error handling, resources) with one-level external links, though all ~219 lines are inlined with no bundle files to offload detail into.	4 / 5
	Total	17 / 20 Passed

Description

82%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong, well-structured description that clearly states purpose, trigger conditions, and example phrases with low conflict risk. The only weakness is a relatively narrow set of concrete actions, which keeps specificity at the midpoint.

Dimension	Reasoning	Score
Specificity	Names the domain (Langfuse deployment) with two concrete actions ('Deploy Langfuse with your application', 'integrating Langfuse into your deployment pipeline') and lists target platforms, but the action set is not comprehensive enough for a 4.	3 / 5
Completeness	Explicitly answers both what ('Deploy Langfuse with your application across different platforms') and when ('Use when deploying Langfuse to Vercel, AWS, GCP, or Docker') with concrete trigger phrases.	5 / 5
Trigger Term Quality	Provides several natural phrases a user would say ('deploy langfuse', 'langfuse Docker', 'langfuse production deploy'), though the 'langfuse X' pattern is somewhat formulaic and misses some synonyms.	4 / 5
Distinctiveness Conflict Risk	Targets a clear niche (Langfuse deployment) with distinct platform-specific triggers, giving minimal overlap risk with other skills.	5 / 5
	Total	17 / 20 Passed

Validation

87%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 14 / 16 Passed

Validation for skill structure

Criteria	Description	Result
allowed_tools_field	'allowed-tools' contains unusual tool name(s)	Warning
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	14 / 16 Passed

Repository: jeremylongshore/claude-code-plugins-plus-skills
Path: plugins/saas-packs/langfuse-pack/skills/langfuse-deploy-integration/SKILL.md
Commit: 8585d6d

Reviewed: 13 days ago

Table of Contents

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