search_docs
Search Appside public developer Markdown; returns source links and excerpts.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes |
Search Appside public developer Markdown; returns source links and excerpts.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes |
Changes observed during successful MCP inspections.
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 bar is lower. The description still adds real value by disclosing the searched corpus (public developer Markdown) and the return shape (source links and excerpts); only ranking, result-count limits, and rate limits are left unstated.
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?
One compact sentence with the action and corpus front-loaded and the return information trailing. Nothing is wasted and nothing is buried.
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 lookup with annotations covering the safety profile and an explicit statement of what is returned, this is close to sufficient. The remaining gap is behavioral detail around result limits and query formulation, which an agent would likely want.
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?
With a single parameter and 0% schema description coverage, the description must carry the load; it does specify the corpus being queried, which implies the query should be documentation-style text. It adds nothing about length limits (schema caps at 200 chars), keyword vs natural-language behavior, or matching semantics.
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 (Search) plus a specific resource and corpus (Appside public developer Markdown), and discloses what comes back (source links and excerpts). It is clearly distinct from siblings get_pricing and get_sdk_snippet in kind, though it does not name them to reinforce the split.
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 when-to-use or when-not-to-use guidance and no reference to the sibling tools. An agent must infer that this is for broad documentation lookup while get_pricing and get_sdk_snippet cover their narrower cases.
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.