Search the ChangeGamer corpus by keyword. Ranks resources by relevance across title, description, tags, category, and body, and returns metadata plus HTML/Markdown/JSON URLs (no body content). Use this to find resources before fetching them with get_resource.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of results (default 10). | |
| query | Yes | Search keywords, e.g. "retrieval augmented generation" or "mcp auth" |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It clearly states that results include metadata and URLs but no body content, which is a key behavioral trait. It does not mention rate limits or auth needs, but the read-only nature is effectively disclosed.
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 that are front-loaded with the action and details, followed by usage guidance. No wasted words; every sentence earns its place.
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?
The description covers purpose, output, and usage guidance. With two parameters fully described in schema and no output schema needed, the description is fairly complete. It could mention that results are ranked by relevance, but that is implied by 'ranks resources by relevance'.
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 100%, so baseline is 3. The description adds value with example keywords for the query parameter, but limit's description is already covered by schema. The examples help an agent form effective queries.
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 uses the specific verb 'Search' and resource 'ChangeGamer corpus', and details that it ranks by relevance across multiple fields and returns metadata with URLs. This clearly distinguishes it from sibling tools like get_resource (fetches content) and list_resources (likely without keyword search).
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 description explicitly instructs to use this tool for searching before fetching with get_resource, providing clear workflow context. It does not give exclusions for when not to use it, but the sibling list implies alternatives.
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.
Most tools are clearly separated by resource type: articles, resources, corpus, stats, and articles. The main ambiguity is the access/pricing/payment cluster (`check_access`, `get_access_info`, `get_pricing`, `get_payment_info`), which agents could confuse despite distinct descriptions.
All tool names follow a consistent `verb_noun` pattern, using `get_*`, `list_*`, and `search_*` prefixes. The naming stays readable and predictable even with broader tools like `search` and `search_resources`.
14 tools is within the typical well-scoped range, and each major retrieval goal has a dedicated tool. It is slightly heavy because the access/pricing/payment information could arguably be consolidated, but it is not bloated.
The server covers discovery, listing, searching, fetching, corpus ingestion, editorial articles, stats, and access/pricing verification. As a read-only content/access server, full CRUD is not expected, though there is no direct category-based batch filter beyond a general search.