The tool that made our AI agent better at using its tools
Kapa has developed an AI agent that assists users in navigating technical documentation. The agent has become the most-used integration, primarily due to its knowledge base search feature. This tool not only answers questions but also helps the agent decide on the next steps in user interactions.
- ▪Kapa's AI agent allows users to ask questions in natural language about their data.
- ▪39.1% of conversations utilized the knowledge base search tool at least once.
- ▪The knowledge base search often acts as a failover for questions that native tools cannot address.
2 outlets in our directory ran this story, first to last over 13 hours. All of the coverage we found sits in one bucket: centre. That one-sidedness is itself worth noticing.
- ▪ gemma4-safe-agent: a tool-using research agent on Gemma 4 e2b — DEV.to (Top)
Hacker News (AI / LLM) files mainly under ai. We currently carry 3,307 of its stories.
Story provenance
Source · retrieval · rights · ranking — open for full record
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Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | Kapa |
| Canonical URL | https://www.kapa.ai/blog/the-tool-that-made-our-ai-agent-better-at-using-its-tools |
| Publication time | Tue, 19 May 2026 19:50:17 +0000 |
| Retrieval time | 2026-05-19T19:54:58.044Z |
| Last seen | 2026-05-19T19:54:58.044Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | wJ8LsEjna01O · 2 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
I am Finn, co-founder of Kapa - we make customer-facing AI assistants on top of technical documentation. Once teams go live with AI chat on their docs their users quickly start asking lots of questions and it can become quite unmanageable to keep track of these. In the past, we’ve built a lot of analytics tooling (like clustering, custom tagging) to try to help our customers make sense of this data. But ultimately none of these are flexible enough to cover all use-cases. So we built an agent into our app. Customers could ask questions about their data in natural language instead of clicking through filters.We expected it to be useful, but secondary. Instead it became our most-used AI integration.Questions per week across our customer-facing AI deploymentsThat usage made us curious.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Kapa.
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