PageRoast
Server Details
AI landing page roast: score /100, 5-second test, top 3 conversion problems quoted from any URL.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP · MCP 2025-11-25
- URL
TDQS
Scored across 1 tool
With only one tool, there is no possibility of confusion with another operation. The tool's purpose is clearly stated and distinct.
The name roast_landing_page follows a clear verb_noun snake_case convention. Although it is the only tool, it is descriptive and consistent.
A single tool is thin for an MCP server, though it matches the narrow, focused purpose of reviewing a landing page. It is borderline rather than clearly appropriate.
The tool covers the core free review workflow: score, first impression, top problems, headline rewrite, and report link. Minor gaps exist around retrieving or managing the full report, but the stated purpose is largely served.
Available Tools
1 toolroast_landing_pageARead-onlyInspect
Free AI conversion review of a public landing page URL: score /100, 5-second-test first impression, top 3 problems quoted from the page, and a headline rewrite. Returns a link to the full report page (where an optional $9 full teardown can be bought). Takes ~20s. Limit 5 free roasts per day per IP.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Public http(s) URL of the landing page to review, e.g. https://example.com |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations only declare readOnly/openWorld; the description adds the operationally important facts an agent actually needs: ~20 second runtime, a hard per-IP rate limit of 5/day, and that the call returns a link to a hosted report where an optional $9 teardown is sold. Those latency/quota/upsell details are exactly the context annotations do not carry.
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 sentences, front-loaded with the deliverable, then the operational caveats. Every clause carries information an agent would otherwise have to discover by calling: outputs, latency, quota, and the paid upsell on the result page.
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?
No output schema exists, so the description must describe the return value – and it does, enumerating the score, first-impression read, quoted problems, headline rewrite, and the report link. Combined with the latency and rate-limit notes, nothing needed to invoke or interpret the result is missing.
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?
Only one parameter and schema coverage is 100% – the schema already says 'Public http(s) URL of the landing page to review, e.g. https://example.com'. The description's 'public landing page URL' restates rather than extends it, so the baseline 3 applies.
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?
Specific verb and resource: an AI conversion review of a landing page URL, with the exact deliverables named (score /100, 5-second test, top 3 problems quoted from the page, headline rewrite). An agent knows precisely what it gets back without opening any other artifact.
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?
Constraints are stated clearly: public http(s) URL only, free, 5 roasts per day per IP, ~20s latency. There are no siblings to differentiate against and no explicit 'do not use for X' case, which keeps it just short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
1 tool update
- First observed
roast_landing_page
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