list_networks
List the affiliate networks with a count of programs on each.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
List the affiliate networks with a count of programs on each.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the behavioral disclosure burden. It clearly implies a read-only listing and specifies the output content, but it does not mention response shape, pagination, ordering, or whether all networks are included. This is adequate but not fully transparent.
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, direct sentence that front-loads the action and resource. Every word contributes meaning, with no filler or 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?
For a parameterless tool, the description gives enough context to select and invoke it: it lists networks and program counts. However, without an output schema, it leaves some ambiguity about response format and whether the list is paginated or complete.
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 input schema has zero parameters, so the baseline is 4. The description does not need to explain parameter meanings since there are none to document.
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 verb ('List'), a clear resource ('affiliate networks'), and a distinguishing detail ('with a count of programs on each'). This separates it from siblings like get_affiliate_program (single program details) and list_categories (category listing).
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 makes the use case clear: when an agent needs an overview of affiliate networks and their program counts. It does not explicitly mention alternatives or exclusions, but the purpose is evident enough for appropriate selection among the given siblings.
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.
Each tool serves a clearly distinct purpose: direct lookup by slug, keyword/filter search, category counts, network counts, and global stats. There is no meaningful overlap or risk of an agent choosing the wrong tool.
All tool names follow a consistent verb_noun snake_case pattern using clear verbs like get, list, and search. The naming is predictable and easy to reason about.
Five tools is well-scoped for a read-only directory server. Each tool covers a distinct access pattern without adding unnecessary surface area.
The server provides complete coverage for a directory: search and filter, individual record retrieval, category/network browsing, and overall stats. Since this is a read-only dataset, no CRUD operations are needed.