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hlee

FeedMob MCP Server

by hlee

list_mobile_apps

Retrieve mobile apps from the FeedMob platform with filters for name, client ID, or tracking party to manage campaigns and performance data.

Instructions

List mobile apps with optional filters.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
searchNoFilter mobile apps whose name contains this substring
client_idNoFilter by client ID
track_party_idNoFilter by tracking party ID (e.g., Adjust, Appsflyer)
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool lists mobile apps with optional filters but doesn't mention whether this is a read-only operation, if it requires authentication, what the return format looks like, or any rate limits. For a tool with zero annotation coverage, this is inadequate for safe invocation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise with a single sentence that efficiently conveys the core functionality. There's no wasted language, and it's appropriately front-loaded with the essential information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has no annotations, no output schema, and the description lacks behavioral details, this is incomplete for safe agent use. While the schema covers parameters well, the description doesn't compensate for missing context about the operation's safety, return values, or usage boundaries.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, meaning all parameters are documented in the schema. The description adds minimal value by mentioning 'optional filters' but doesn't provide additional context beyond what the schema already specifies for each parameter. Baseline 3 is appropriate when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('List') and resource ('mobile apps'), and mentions optional filtering capability. However, it doesn't specifically differentiate this tool from sibling tools like 'get_mobile_app' or other list tools, which would require a more specific scope or distinction.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like 'get_mobile_app' or other list tools. It mentions optional filters but doesn't specify scenarios or prerequisites for usage, leaving the agent to infer context without explicit direction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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