tech-sensemaking
tech-sensemaking is a Market & industry research skill for AI agents, published by gnurio in the nurijanian-skills repository on GitHub. Skillspace rates tech-sensemaking D (66/100) and it passed the safety scan; the rating is based on static analysis only.
Analyze technology announcements to surface non-obvious strategic implications using Verbalized Sampling. Works against any context: a business, product, codebase, feature branch, personal project, career, or exploratory domain. Use when a new technology, feature, or capability is announced and you want to understand what new outcomes, affordances, and competitive levers it creates — beyond the obvious hot takes. Triggers on: "analyze this announcement", "what does this mean for us", "tech sensemaking", "new feature dropped", "what can we do with this", "sensemaking on this", "strategic implications of", or any request to evaluate a technology change strategically. Category: Product Strategy
- Grade
- D
- Quality
- 66 / 100
- Safety
- Passed
- GitHub stars
- 82
Unproven: rated by static analysis only, not yet compared head-to-head.
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.
Our review
- Architecture
- 84 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- No issues found
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 0 collections
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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