Anonymised evidence that the system works, plus how to see it running. Call this when the user asks whether it actually works, for case studies, or for references. Client names are never returned.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description carries the full burden. It discloses that client names are never returned and that the tool also provides a way to see the system running, which is useful behavioral context. However, it could specify the exact output format or any side effects, but for a zero-param read-like tool this is acceptable.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two succinct sentences clearly state what the tool returns, when to use it, and a key privacy guarantee. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no parameters and no output schema, the description covers its purpose, usage triggers, and behavioral guarantee (anonymity). It also hints at the deliverable ('how to see it running'), making it self-sufficient for the AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool takes zero parameters, and the schema has 100% coverage with no properties. Baseline for 0 params is 4, and the description does not need to explain parameters that do not exist.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear purpose: providing anonymised evidence that the system works, along with instructions for seeing it running. It distinguishes itself from sibling tools like get_demo_transcript by focusing on proof-of-function rather than specific demo content.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly says when to call: when the user asks whether it works, for case studies, or for references. It does not mention when not to use it or name alternatives, but the context given is strong.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct action in the sales demo workflow—information retrieval, demo setup/progression, email demo polling, transcript retrieval, or booking. There is no overlap; even the three demo-related tools have clear lifecycle boundaries (start/continue/transcript).
All tool names follow a verb_noun pattern using snake_case, with consistent verb choices (get_* for informational, start_* for demos, etc.). No mixed conventions or vague verbs.
With 10 tools, the set is well-scoped for a sales/demo assistant, covering information, demos, access management, and booking without redundancy or bloat.
The surface covers the full sales journey: learn about the product (positioning/pricing/proof), try it (text/email demos), manage demo access, and book a call. No obvious dead ends—each demo has appropriate lifecycle support (start/continue/transcript/poll).
