Lists one page of accessible Google BigQuery projects, handling first-use Google sign-in and saving a local token for later calls.
List one page of accessible projects. First use may open Google sign-in and save a local token.
| Name | Required | Description | Default |
|---|---|---|---|
| account | No | ||
| page_size | No | ||
| page_token | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover the safety profile (readOnly, idempotent, non-destructive, openWorld), so the description's value is in the extra disclosures: the call returns a single page rather than the full set, and first use has an interactive auth side effect that writes a local token. That side-effect warning is genuinely beyond what the annotations say and matters for non-interactive callers. It doesn't cover error modes or what happens if the sign-in is declined.
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 short sentences, zero filler, with the core action front-loaded before the auth caveat.
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?
The output schema means return values needn't be explained, and the auth caveat covers the biggest surprise. But with three parameters at 0% schema coverage, leaving `account` (multi-account selection) and the page_token continuation flow entirely undescribed leaves the agent guessing on a tool it will likely call first.
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?
Schema description coverage is 0%, so the description must carry parameter meaning, and it largely doesn't. "One page" vaguely gestures at page_size/page_token but never explains page_size's 1–1000 bounds or how to continue via page_token, and the `account` parameter is never mentioned at all.
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?
States a specific verb and resource ("List one page of accessible projects") and the sibling names (list_datasets, list_tables) make the resource level unambiguous. It doesn't say these are BigQuery projects or that projects are the top-level container for datasets — the annotation title carries that — but an agent can still distinguish it from siblings.
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?
No explicit when-to-use or when-not guidance relative to siblings, but it does disclose a real prerequisite: first use may trigger an interactive Google sign-in and persist a local token. That is useful context an agent needs before calling, though it is a prerequisite rather than routing guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.