Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden and delivers extensively: re-calling returns the SAME password and does not reset data, /app exists only on the published site and not the preview origin, the backend is Python/Flask ONLY and sandboxed with no internet, and it requires a plan that includes backends. These are precisely the behavioral traits that prevent an agent from giving users destructive or false advice.

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?

The description is long, but nearly every sentence earns its place: purpose, trigger conditions, idempotency warning, deployment quirk, tech constraints, and plan gating are all decision-relevant. It loses a point for being a single dense wall of text rather than structured sections, which would improve scannability.

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 high-complexity tool with no annotations, the description covers all operational dimensions an agent needs before calling: outcome, prerequisites (plan requirement), failure handling ('say so plainly and offer the data-collection form'), environment behavior (published vs preview), and follow-up tool routing. An output schema exists so return-value documentation is already covered.

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 coverage is 0%, so the description must compensate. It contextualizes both parameters implicitly — project_guid via 'same project' in the idempotency note, and collection via the 'from orivox import collections' helper and the mention of the admin page listing submissions — but never explicitly defines what the `collection` parameter controls or what values it accepts. The context helps an agent guess correctly, but the mapping is left implicit.

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 opens with a specific verb-resource statement: 'Give this project a real Python backend, served at /app on its own site — so it can have a genuine LOGIN and admin area.' It clearly distinguishes the tool from siblings like create_database and build_site by anchoring on authentication and admin capabilities a static page cannot provide.

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?

Explicit trigger conditions are given: 'Reach for this when the user wants something a static page cannot do: a password-protected page, an admin panel... anything needing a session.' It also names an exclusion ('A client-side password is not a login and must never be offered as one') and routes to related siblings for follow-up work (write_backend_file, read_backend_file, list_backend_files, read_backend_logs).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.