Show HN: Interview your analysts instead of auto-generating a semantic layer
I’ve spent the last year building context for AI analysts in the mid-market. I’ve open sourced a library from my learnings, along the same principles of the Matt Pocock skills. Principles: * Claude / Codex / Cursor etc are great data agents - you just need context to enable them to answer business questions correctly. * Much of the important context lives in analysts heads' * Context must be maintainable (short, human readable - markdown and yaml) * Added context should be load bearing, not repe
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Recorded metrics
points · 5 votes
2026-10-29 01:45:32.757Z
cumulative since publication
Research analysis
Project record
Repository: nodal-data/nodal-context. Source account: I’ve spent the last year building context for AI analysts in the mid-market. I’ve open sourced a library from my learnings, along the same principles of the Matt Pocock skills. Principles: * Claude / Codex / Cursor etc are great data agents - you just need context to enable them to answer business questions correctly. * Much of the important context lives in analysts heads' * Context must be maintainable (short, human readable - markdown and yaml) * Added context should be load bearing, not repe
Observed adoption & comparisons
Source votes: 5 votes (Oct 29, 2026 UTC; cumulative since publication); previous same-scope observation: 4 (Oct 28, 2026 UTC). These observations do not establish demand growth. Recent records to compare: “Show HN: Cerea – yet another self-hosted LLM chat front end” (Show HN, Nov 5, 2026); “Show HN: Lantern Lattice – the call graph from your compiler, for coding agents” (Show HN, Nov 5, 2026). Shared themes are navigation hints; they have not been verified as the same need or independent corroboration.
Adoption decision
Evaluate it against the tool or manual workflow it would replace. The stored record supports discovery; it does not yet establish reliability, lower operating cost or commercial adoption.
Unverified requirements
Not verified: license permissions, required hardware, installation steps, maintenance status and a representative task with its failure cases.
Next test
Choose one real task and a current alternative. Record the commit, environment, input, output, elapsed time and failure behavior; retain the result before recommending adoption.