AI agent

Agent tool calls

The agent picks tools, passes args, reads results, decides next steps — visible in the chat stream.

How tool calls actually work

When you send a prompt, the agent ships every available tool schema to the model. The model can answer directly or "call a tool first." After the result comes back, the loop continues — sometimes for many rounds.

Kition renders each round as a collapsible card: which tool, what arguments, what it returned, how many tokens. This is the difference between an agent and a black box.

Built-in tools

  • Read / Write / Edit — file ops, scoped by path glob
  • Bash — shell execution, defaults to vault root
  • web_search / web_fetch — web search and fetch
  • browser_open — real Chromium browser automation
  • table_query / table_upsert / table_delete — table ops
  • grep / glob — cross-file search
  • MCP — third-party extensions (GitHub, Jira, custom tools)

What a real call looks like

You say: "Find docs with TODOs from the last 7 days and list them in a table." The agent typically greps, then reads, then table_upserts, then sends a confirmation. Every step is expandable in the panel.

> tool: grep
  pattern: "TODO|FIXME"
  path: "**/*.md"
  result: 14 matches across 6 files

> tool: Read
  path: "projects/onboarding.md"
  result: 2.3 KB

> tool: table_upsert
  table: "todos"
  rows: [
    { file: "projects/onboarding.md", text: "wire up SSO", owner: "?", due: "?" },
    ...
  ]
  result: 14 rows inserted

See every step, edit any step

  • Click retry — rerun with the same args
  • Click edit args — adjust and run again
  • Click skip — fake success and let the agent continue
  • Click stop — halt the whole loop

Parallel tool calls

When tool calls have no dependencies, the agent dispatches them in parallel — e.g. reading five files at once. This is the main speed gap between Kition and "one-step-at-a-time" agents.

Tune the fan-out in Settings → Agent → Concurrency: lower it to be polite to providers, raise it to pin your local CPU.

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Kition is a local-first AI workspace. Markdown documents, structured tables, and an AI agent — running on your own machine, against the model provider you choose.