RetentionRail
Server Details
Research competitors and trends, write scripts, and screen videos before you publish.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP · MCP 2025-11-25
- URL
TDQS
Scored across 2 tools
The two tools have clearly distinct purposes: one returns a sample screening report, the other provides onboarding information. No overlap or confusion.
Both use snake_case, but the conventions differ: get_started is a verb phrase while demo_screening_report is a noun phrase. Readable but not a consistent verb_noun pattern.
Only 2 tools, which is thin for a server representing a screening service. It feels under-scoped even for an onboarding-focused surface.
The server only offers a demo report and signup info; core operations like submitting footage or retrieving a real screening report are absent. The description even references get_screening_report, which is not included.
Available Tools
2 toolsdemo_screening_reportDemo screening reportARead-onlyIdempotentInspect
Return a real precomputed RetentionRail pre-publish screening report (a 1:00 YouTube Short) in the same shape a keyed workspace receives from get_screening_report. Sample data, not the caller's footage.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| cost | No | |
| data | No | |
| error | No | |
| status | Yes | |
| summary | Yes | |
| evidence | No | |
| warnings | No | |
| confirmation | No | |
| evidence_receipt | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, non-destructive, and closed-world, so the safety profile is covered. The description adds genuinely useful behavioral context beyond that: the data is precomputed sample data, not the caller's footage, which an agent must know to interpret results correctly. It does not describe payload size or pagination, but none is expected.
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 compact clauses, front-loaded with what is returned and immediately qualified by the sample-data caveat. Every phrase earns its place with no redundancy.
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?
An output schema exists so return-shape details need not be repeated, and the description supplies the one non-obvious fact an agent needs (this is static demo data mirroring the keyed report). Nothing required for correct invocation 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?
The tool takes zero parameters, so the baseline is 4. The description correctly implies no input is required and gives no misleading parameter guidance.
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 (Return) and resource (precomputed RetentionRail screening report) with concrete detail about what the payload is (a 1:00 YouTube Short). It differentiates itself from the keyed get_screening_report by explaining the report is sample data, though it does not reference its listed sibling get_started.
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?
Implies the usage context clearly: this is demo/sample data rather than the caller's footage, so it is the tool to reach for when a real keyed report isn't appropriate. It stops short of an explicit when-to-use/when-not statement or naming an alternative by name in a routing sense.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_startedGet started with RetentionRailARead-onlyIdempotentInspect
Return the signup URL, the API key URL, the install command that includes a key, and the tools a key unlocks.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| cost | No | |
| data | No | |
| error | No | |
| status | Yes | |
| summary | Yes | |
| evidence | No | |
| warnings | No | |
| confirmation | No | |
| evidence_receipt | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=false, and destructiveHint=false, so the safety profile is fully covered by structured data. The description's addition is limited to enumerating returned items, which overlaps with the existing output schema rather than adding behavioral context such as auth requirements or rate limits.
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?
A single front-loaded sentence that lists the concrete payload with zero filler. Every clause names something the caller receives.
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?
With rich annotations, an output schema documenting the return shape, and no input parameters, the description is essentially sufficient for correct invocation. The only gap is the absence of routing guidance relative to the sibling tool.
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 no parameters, so the baseline is 4 and there is nothing further for the description to clarify. Schema description coverage is trivially 100%.
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 concretely what the tool returns: a signup URL, an API key URL, an install command containing a key, and the tools a key unlocks. That is far more specific than the name 'get_started' alone, so an agent knows this is the onboarding/bootstrap-info tool. It does not explicitly differentiate from the sibling demo_screening_report, which keeps it from a 5.
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?
There is no statement of when to call this versus the sibling tool, no prerequisites, and no indication of whether it should be called first in a session. The description is purely descriptive of outputs and leaves usage entirely to inference.
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.
2 tool updates
- First observed
demo_screening_report - First observed
get_started
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