Get a cheatsheet
get_cheatsheetJump straight to a cheatsheet by topic (docker, cloudformation, cost, aurora, kubernetes, …) and get its full text.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| topic | Yes | Cheatsheet topic or name. |
get_cheatsheetJump straight to a cheatsheet by topic (docker, cloudformation, cost, aurora, kubernetes, …) and get its full text.
| Name | Required | Description | Default |
|---|---|---|---|
| topic | Yes | Cheatsheet topic or name. |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover the safety profile with readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds the useful detail that the tool returns the full text of the cheatsheet, but it does not disclose behavior for unknown topics, formatting, or any error handling. This is adequate given the annotations but not rich.
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 a single, tightly written sentence that front-loads the action and resource, followed by example topics in parentheses. Every word contributes to meaning, with no redundancy or filler.
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 one-parameter, read-only tool with no output schema, the description gives the input semantics and the nature of the return value ('full text'), which is enough for correct invocation. It omits exact topic-matching rules and not-found behavior, but those are minor for such a simple interface.
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 100% ('Cheatsheet topic or name.'), so the baseline is 3. The description adds value by providing concrete examples of valid topics (docker, cloudformation, cost, aurora, kubernetes) and contextualizing the 'by topic' behavior, which helps an agent choose an appropriate value beyond the bare schema definition.
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 specific action ('jump straight to... get its full text') on a concrete resource (a cheatsheet) with a topic filter. This makes it immediately distinguishable from sibling tools like list_cheatsheets (which enumerates) and read_post (which returns a post, not a cheatsheet).
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?
The phrase 'jump straight' implies the tool is for when the agent already knows the topic and wants the full cheatsheet text, but there is no explicit contrast with alternatives such as list_cheatsheets or browse_by_tag. No conditions, exclusions, or 'when not to use' guidance are provided, leaving the decision mostly to inference.
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.