Modern agents often have access to dozens or hundreds of tools — between MCP servers, OpenAPI specs, and connectors, the catalog grows fast. But every tool the agent might call eats prompt tokens, every turn, whether the agent uses it or not. Deferred Tools fix that: tool definitions stay out of the system prompt until the agent explicitly asks for them.Documentation Index
Fetch the complete documentation index at: https://hastekit.ai/docs/llms.txt
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How it works
A deferred tool is registered with HasteKit but not exposed in the system prompt by default. Instead, the agent sees a single meta-tool —tool_search — that lets it discover and load tools on demand:
- The agent calls
tool_search("calendar"). - HasteKit returns a short list of matching tool names and one-line summaries.
- The agent calls
tool_load(["GoogleCalendar.CreateEvent"]). - The full schema of that tool is now in scope and the agent can call it.
Marking tools as deferred
Available on every tool type that supports filtering:- MCP Servers — Deferred Tools field (comma-separated tool names).
- API Servers — flag specific operations.
- Connectors — flag specific actions.
- Provider Tools — toggle on a per-tool basis.
When to defer a tool
- Big catalogs — anything past ~20 tools starts to crowd the prompt and degrade tool-call accuracy.
- Specialty tools — tools the agent only needs in narrow cases (e.g.
Jira.TransitionIssueis only relevant once the user mentions tickets). - Heavy schemas — tools whose input schemas are huge (deeply nested objects, long enums) cost more tokens to keep loaded.
When NOT to defer
- Always-needed tools — if the agent is going to use the tool on most runs, deferring just costs an extra round-trip every time.
- Tools the agent should consider proactively — discovery only happens when the agent thinks to search; if the right answer is “use tool X” and the agent doesn’t know X exists, it won’t find it.