New to the Context Store, or want the full picture of how it shapes each feature? Start with Tailoring Klarity for non-standard use cases. This page is the practical refinement guide for a Context Store that’s already set up.
Quick refresher
The Context Store is the business-knowledge layer the AI applies automatically. Every rule has a scope (User / Workspace / Organization — who it affects) and a feature target (All Features, or a specific one like Advisor, Companion, Signals, Operations — where it applies). Effective context for any interaction is all applicable rules combined.When to refine it
Revisit your Context Store when:- Outputs are consistently off — Advisor reports miss a constraint you care about, Companion captures miss your terminology, Signals surface the wrong things. A recurring miss usually means a missing or vague rule.
- Your business changes — new ERP or systems, a reorg, a new compliance requirement, a new market or entity. The AI only knows what the Context Store tells it.
- You’ve added a new use case — rolling out a feature to a new team or function often needs context that wasn’t relevant before.
- A rule is doing too much (or too little) — an “All Features” rule that’s affecting features it shouldn’t, or a rule too vague to change behavior.
Why refining matters
Good context is the difference between generic AI and AI that’s grounded in your business. But the Context Store is shared and always-on, so a careless rule can quietly degrade quality everywhere — refining is as much about removing and tightening as adding.How to refine — safely
- Find the right scope and feature. Change behavior for one feature? Target that feature, not “All Features.” Just for you? Use User scope. This limits the blast radius if the change has side effects.
- Write specific, actionable rules. “Limit Advisor to 5 recommendations, each one paragraph” beats “keep it concise.” Vague rules produce inconsistent results.
- Distill, don’t paste. Don’t drop whole documents in — extract the few points the AI needs every time. Overstuffed context crowds out the AI’s ability to reason about the actual request.
- Check for conflicts first. Before adding, review existing rules at “All Features” and higher scopes. Contradictory rules (e.g., “be comprehensive” vs. “under 500 words”) force arbitrary trade-offs.
- Save, then verify. Hard-refresh, open the affected feature, run a quick test interaction, and confirm the behavior changed the way you intended.
Common pitfalls to avoid
- The blast radius problem. A Workspace rule under “All Features” hits every feature for every user. A poorly worded one can silently degrade Advisor, Companion, and Signals at once. Use feature-specific targeting unless the rule is truly universal.
- Contradictory rules across scopes. Audit before adding so lower-scope rules complement, not fight, higher-scope ones.
- Overstuffing. Keep each scope + feature combination concise (a few hundred words). More context isn’t better — it competes with the user’s actual request.
When it’s not behaving
If a rule still isn’t behaving as expected, reach out through the in-app chat or to your Klarity team.
Where to go next
Tailoring Klarity for non-standard use cases
The full picture: Context Store + custom templates.
Running an Advisor analysis
Where many tuned behaviors show up.