Tool Search — Load Tools on Demand

Imagine carrying a 3000-key keychain just to open your front door. That’s what happens when your AI assistant has hundreds of external tools loaded into its working memory — every tool comes with a “user manual” (JSON Schema), and the AI has to read all of them, even for a trivial task.

Tool Search fixes this by giving your AI a smart warehouse manager: it only keeps a few everyday tools in hand, and fetches the rest when actually needed.

Why Bother?

When you connect many external services (GitHub, Cloudflare, Linear, etc.) to Hermes Agent, each one adds a chunk of documentation to the AI’s context window. That’s precious “working memory” — and it gets diluted by irrelevant instructions. The result? Slower responses, worse reasoning, and sometimes the AI “forgets” your core instructions entirely.

How It Works

With Tool Search enabled, the AI no longer sees all tools directly. Instead, it sees three “bridge” tools:

tool_search(query, limit?)     # Search the tool catalog
tool_describe(name)            # Read a tool’s full manual
tool_call(name, arguments)     # Execute a tool

A typical flow looks like this:

# 1. Find the right tool
tool_search("create a github issue")
# → returns matching tools

# 2. Read its manual
tool_describe("mcp_github_create_issue")
# → shows required parameters

# 3. Call it
tool_call("mcp_github_create_issue", {"title": "Fix bug", "body": "..."})
# → issue created successfully

Key point: when the AI calls tool_call, the system “unwraps” the bridge and runs the real tool. All security checks and approval workflows still apply — the AI simply sees less, but does the same.

When Does It Kick In?

Tool Search uses a tiered disclosure strategy:

Level	Condition	What the AI sees
0	No external tools	All tools shown directly, no bridge
1	Few tools	Bridge + short list (name + one-line description)
2	Many tools (e.g., Cloudflare’s 3300)	Bridge + one-line summary per server (name + tool count)

Nice touch: if you mix a small tool (Linear) with a giant one (Cloudflare), the system keeps Linear’s full list and only collapses Cloudflare into a single line — no blanket hiding.

Core Tools Always Stay

Hermes’ built-in tools (terminal, file I/O, web search) are never lazy-loaded. They stay directly available because they’re the AI’s core capabilities. Only external MCP tools and plugins get shelved into the “warehouse.”

Final Thoughts

Tool Search is like giving your AI a just-in-time inventory system — it solves the “attention dilution” problem when tool count explodes. Practical tip: if your AI feels sluggish or off-target on simple tasks, check how many external tools are attached. Enable Tool Search and you’ll likely see a noticeable boost in both speed and accuracy. For everyday use, keep your tool count under 10 for the smoothest experience.