pi-interview-tool: Interactive form tool for pi-agent to gather user responses with keyboard navigation, themes, and image

by nicobailon · Agent Tool · ★ 316

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: SAFE · quality 67/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

Quick Facts

Stars316
Forks21
LanguageTypeScript
CategoryAgent Tool
Quality Score67/100
Last Updated2026-09-27
Created2026-01-02
Platformsnode
Est. Tokens~18k

About pi-interview-tool

Interview Tool A custom tool for pi-agent that opens an interactive form to gather user responses to clarification questions. On macOS, uses Glimpse to render in a native WKWebView window; falls back to a browser tab on other platforms. https://github.com/user-attachments/assets/52285bd9-956e-4020-aca5-9fbd82916934 Installation Restart pi to load the extension.

Compatible Skills

These tools work well together with pi-interview-tool for enhanced workflows:

  • overstory — semantic(0.17)+complementary+same_lang+similar_pop+shared_platform (51%)
  • pi-tool-display — semantic(0.17)+complementary+same_lang+similar_pop+shared_platform (51%)
  • wordpress-agent-skills — semantic(0.17)+complementary+same_lang+similar_pop+shared_platform (51%)
  • tweakcc — semantic(0.16)+complementary+same_lang+similar_pop+shared_platform (51%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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