Surface 3-7 data-grounded insights from user-supplied notes or datasets.
npx skills add https://github.com/jbrukh/skills --skill surface-insight
Please help me install this Agent Skill. Skill: surface-insight Source: https://github.com/jbrukh/skills/tree/main/skills/surface-insight Command: npx skills add https://github.com/jbrukh/skills --skill surface-insight
Take data, observations, or notes and surface insights that were hiding in the data all along. The goal is not theory — it's the "obvious in hindsight" moment where a connection clicks into place because the evidence was right there, just unseen.
Provide your data or notes and I will surface non-obvious insights that click into place.
High-intent search queries and answers about installing and using this skill.
To find hidden insights in your data, supply your raw notes or datasets to an analysis process that enforces data-first discovery and grounds every conclusion in concrete evidence. This yields 3-7 non-obvious, verifiable insights without speculation.
Data-first discovery is an analysis phase that extracts connections by strictly grounding every finding in concrete data points supplied by the user. It prevents speculation by enforcing that each insight cites specific evidence rather than theoretical assumptions.
To extract non-obvious connections from raw observations, process your data through structured intake and insight development phases. This enforces a grounding rule requiring every connection to cite specific data points, ensuring verifiable conclusions.
Yes, you can use bullet points and informal notes for data synthesis. The analysis process accepts observations, notes, or datasets as input, guiding them through phase-based intake to surface 3-7 well-supported insights grounded in your specific evidence.
The best way to verify insights derived from a dataset is to enforce a grounding rule where each conclusion cites or quotes specific data points. This structured synthesis yields verifiable conclusions and guards against unsupported speculation.
Yes, data synthesis works without formatted datasets. You can supply bullet points, informal notes, or raw observations, and the phase-based intake process will extract 3-7 well-supported insights grounded strictly in the evidence you provide.
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