get_lead_enrichmentGet extracted company, role, timeline, and budget context from conversations.
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | ||
| client | No | Agency only: target a managed client org by its id to query that client's data. Omit for your own. | |
| has_company | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / clientAdded value: +{
+ "description": "Agency only: target a managed client org by its id to query that client's data. Omit for your own.",
+ "type": "string"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true, and the description's 'Get' aligns with that. The description adds minimal behavioral context (e.g., source is conversations) but does not disclose filtering behavior, time windows, or output structure. It is not contradictory, but adds only marginal value beyond annotations.
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 concise sentence with no padding or repetition. It front-loads the core action and result, earning a high score for efficiency.
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 simple read-only tool with optional filters, the description is adequate but lacks important context like default behavior (days=30), how has_company affects results, and what 'enrichment' means in practice. The schema helps, but the description doesn't fully round out the tool's behavior.
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 schema covers only 33% of parameters with descriptions (only 'client' has one), and the description does not explain 'days' or 'has_company' at all. It adds no meaning beyond what the schema already provides, failing to compensate for the low coverage.
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 clearly states it retrieves extracted company, role, timeline, and budget context from conversations, which is a specific verb+resource combo. It distinguishes itself from sibling tools like get_hot_leads or get_meddic_summary by focusing on enrichment context.
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?
No guidance is provided on when to use this tool versus the listed sibling tools. It only states what it does, without mentioning use cases, exclusions, or alternatives, leaving the agent without explicit selection criteria.
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 distinct, but get_conversations and search_by_intent both return conversations, and get_hot_leads vs get_lead_enrichment have some overlap. Descriptions clarify their specific purposes, so ambiguity is minimal.
The majority of tools follow the get_* pattern, but search_by_intent deviates. Otherwise, naming is consistent and readable.
With 8 tools, the count is well-scoped for the server's purpose. Each tool focuses on a distinct aspect of buyer intent, from summaries to specific searches, without unnecessary bloat.
The server covers core needs: overview, listing, detail, enrichment, MEDDIC summary, knowledge gaps, and search. Missing are non-read operations and a general lead list (only hot leads), but these are minor gaps for an analytics-focused server.