orlob-discovery-framework

orlob-discovery-framework is a Discovery & demos skill for AI agents, published by ScientiaCapital in the skills repository on GitHub. Skillspace rates orlob-discovery-framework B (81/100) and it passed the safety scan; the rating is based on static analysis only.

Chris Orlob's 5-step discovery framework applied to Epiphan — business problem → cause analysis → negative impact → future state → close. Per-vertical root causes, calibrated question bank, MEDDIC integration, and the 0-3 discovery scoring rubric used by sdr-call-coaching. Use when: discovery framework, orlob discovery, discovery questions, cause analysis, business problem discovery, how to run discovery.

Grade
B
Quality
81 / 100
Safety
Passed
GitHub stars
25

Unproven: rated by static analysis only, not yet compared head-to-head.

Not launch-quality. It is graded B with a clean safety verdict, but our quality filters exclude it: a model that read it found it written only for the repository it lives in. So it is not in our launch-quality set, the skills our MCP server searches and recommends. How launch-quality is decided

Our two independent classifiers differ on this skill's category, so treat the placement as provisional.

This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.

View source on GitHubScientiaCapital/skills

Our review

Architecture
100 / 100
Maturity
Structured: ships references or scripts
Security scan
No issues found
License
Not declared. Check the repository before reusing it.
Adoption
Adopted by 0 other repositories, in 0 collections
Scope
Repo-internal: written for the repository it lives in. Discovery framework applied specifically to Epiphan products and verticals

Not checked yet

  • Not judged on the rubric yet (not a contender in its category)
  • No blind task eval yet
  • Sibling files (scripts, references) not fetched; security scan covers SKILL.md only

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