mixpanel-headless-setup

This skill installs mixpanel_headless, pandas, numpy, matplotlib, seaborn, networkx, anytree, scipy (and pyarrow on Python 3.11+), then verifies Mixpanel credentials. It should be invoked when setting up a new environment for Mixpanel data analysis, when dependencies are missing, or when configuring service account or OAuth credentials for the first time.

Quality

90%

Does it follow best practices?

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Securityby

Passed

No findings from the security scan

Quality

Content

88%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.

The body is highly actionable with a clear, validated multi-step workflow and concrete commands for every path. Structure and progressive disclosure are good but could be tightened by relocating some inlined flag/region detail into this skill's own reference files.

Suggestions

Tighten rhetorical phrases such as 'The frictionless one-shot path' and 'This is the recommended mode for non-interactive contexts' to save tokens without losing clarity.

Move the full mp login flag list and the us/eu/in region matrix into a local references file (e.g. references/auth-options.md) and link to it, keeping the body as an overview.

Consider co-locating or mirroring the analytical-frameworks.md and python-api.md references within this skill's own references/ so the setup skill is self-contained.

Dimension	Reasoning	Score
Conciseness	Mostly lean and task-focused with no concept filler Claude already knows, but a few phrasings ('The frictionless one-shot path', 'This is the recommended mode for non-interactive contexts') and minor redundancy across env-var sections could be trimmed.	4 / 5
Actionability	Provides fully executable, copy-paste-ready commands and code (setup.sh, auth_manager.py session/test, mp login, export-bridge, env-var exports, mp.Workspace examples) covering local, remote, expired-token, and bearer-token cases.	5 / 5
Workflow Clarity	Multi-step setup is clearly sequenced with explicit validation (package import check, result.ok dispatch) and feedback loops for error recovery (token-expired re-auth/bridge re-export, needs_account/needs_project/error state dispatch).	5 / 5
Progressive Disclosure	Well-organized overview with clearly signaled one-level-deep references (analytical-frameworks.md, python-api.md) and a real referenced bundle (scripts/setup.sh), but those references live in a sibling skill and some inlined flag/region detail could be split into this skill's own references.	4 / 5
	Total	18 / 20 Passed

Description

92%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.

The description is strong: it states concrete install and credential-verification actions in third person and gives three explicit invocation triggers. Its only weakness is slightly technical rather than user-natural phrasing on a few Mixpanel synonyms.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions with granular, version-gated specificity ('installs mixpanel_headless, pandas, numpy, matplotlib, seaborn, networkx, anytree, scipy (and pyarrow on Python 3.11+)', 'verifies Mixpanel credentials'), matching the comprehensive-coverage anchor.	5 / 5
Completeness	Explicitly answers both what (install deps + verify credentials) and when (three concrete enumerated invocation scenarios), matching the clear-what-and-when-with-concrete-trigger-phrases anchor.	5 / 5
Trigger Term Quality	Good coverage of natural when-triggers ('setting up a new environment', 'dependencies are missing', 'configuring service account or OAuth credentials'), but a few natural Mixpanel-user phrasings and synonyms are absent, fitting just below the comprehensive anchor.	4 / 5
Distinctiveness Conflict Risk	Scoped to a clear Mixpanel-headless niche with Mixpanel-specific triggers ('mixpanel_headless', 'Mixpanel credentials'), giving minimal conflict risk with other skills.	5 / 5
	Total	19 / 20 Passed

Validation

93%

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 — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
relative_links	Relative link issues: 2 suspicious	Warning

	Total	15 / 16 Passed

Repository: openai/plugins
Path: plugins/mixpanel-headless/skills/setup/SKILL.md
Commit: 1e28582

Reviewed: 9 days ago

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