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qp-exa-dynamic

Web Tools Updated 2026.09.11

Run the following command in DeepSeek Harness:

dsh plugin install Geighlord007/qp-exa-dynamic

Paste the following prompt into your AI chat to install this plugin:

Run dsh plugin install Geighlord007/qp-exa-dynamic in DeepSeek Harness (source at https://github.com/Geighlord007/qp-exa-dynamic), then override the web search row and provide your Exa API Key.

About this plugin

The first-party Exa search provider in DeepSeek Harness has a structural gap: its request body hardcodes highlightsPerUrl and never sends the Exa-Beta header, so Dynamic Highlights—a feature where Exa runs a single forward pass and allocates a shared context budget across all results—simply cannot be reached. Exa responds with HTTP 400. qp-exa-dynamic fixes both issues, ships with Dynamic Highlights on by default, and replaces the inert highlightsPerUrl knob with maxCharacters, which actually works when dynamic mode is off.

The plugin exposes all eight Exa retrieval types, from 464 ms keyword to 18 s deep-reasoning, and provides a composer-level /exa command to toggle highlights, switch retrieval type, and adjust result count at runtime—no restart needed. It also registers a second, model-facing tool called exa_search that owns its own per-call maxResults argument, letting the model request up to 50 sources in a single query without forking an agent preset to raise the dsh-tool-web ceiling that clamps web_search at 8.

It is built for developers already searching the web through DeepSeek Harness who find the default context quality too coarse, the source count too rigid at 8, or the retrieval type locked to a stale three-option subset. If you want to dial between keyword speed and deep reasoning mid-conversation, or let the model itself negotiate how many sources to pull per question, this plugin is exactly that control surface.

Use Cases

  • Toggle retrieval type or adjust result count mid-conversation via the /exa command without restarting
  • Use Dynamic Highlights so Exa allocates a shared context budget by information density, cutting redundant tokens
  • Let the model fetch anywhere from 8 to 50 sources per call through the exa_search tool

Best For

  • Developers on DeepSeek Harness who want sharper search context than the default provider offers
  • Engineering teams building RAG pipelines who need granular control over retrieval type and result count
  • Agent developers who outgrew the 8-source web_search ceiling and want per-call flexibility without forking a preset