get_deals_pipeline
Show the user's Xmagnet deals pipeline with stage breakdown, values, and win rate analytics.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| status_filter | No | open | |
| include_analytics | No |
Show the user's Xmagnet deals pipeline with stage breakdown, values, and win rate analytics.
| Name | Required | Description | Default |
|---|---|---|---|
| status_filter | No | open | |
| include_analytics | No |
Changes observed during successful MCP inspections.
Input schema / properties / include_analytics / descriptionRemoved value: -"Whether to include win-rate and average-deal-size analytics"Input schema / properties / status_filter / descriptionRemoved value: -"Filter deals by status — default is open deals only"Input schema / properties / include_analytics / descriptionAdded value: +"Whether to include win-rate and average-deal-size analytics"Input schema / properties / status_filter / descriptionAdded value: +"Filter deals by status — default is open deals only"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, establishing safety. The description adds valuable behavioral context by specifying the output content (stage breakdown, values, win rate analytics) and user scoping, going beyond the annotations without contradicting them.
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, perfectly sized sentence that front-loads the main purpose and key output elements. No wasted words.
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 tool has no output schema and only minimal parameter information in the schema. The description explains the high-level output but leaves important behavior unclear, such as how status_filter changes results (especially the default 'open' filter) and what happens when include_analytics is false. It is adequate but not fully 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?
Schema description coverage is 0%, so the description must compensate for parameter meaning. It does not mention status_filter or include_analytics at all, leaving the agent to rely solely on the enum and defaults in the schema. This is a significant gap for a tool with two optional parameters.
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 'Show the user's Xmagnet deals pipeline with stage breakdown, values, and win rate analytics' clearly identifies a specific verb ('Show'), resource ('deals pipeline'), and includes distinguishing details (stage breakdown, values, win rate analytics) that differentiate it from sibling tools like get_ghost_pipeline or get_dashboard_stats.
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 provides clear context on what the tool does and its scope (user's pipeline), allowing an agent to infer appropriate usage. However, it does not explicitly mention when not to use it or name alternative tools, so it falls short of a 5.
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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