predictive_motion_causality_info
Explain AlpineLead's deterministic Motion + Causality shadow layer. Uses 0 credits and 0 AI calls.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Explain AlpineLead's deterministic Motion + Causality shadow layer. Uses 0 credits and 0 AI calls.
| 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?
With no annotations provided, the description carries the full behavioral burden. It discloses that it uses 0 credits and 0 AI calls, which is a useful cost note. However, it does not explicitly state that it has no side effects, though 'explain' suggests read-only. This is a minimal but acceptable disclosure for an informational tool.
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 sentence that immediately states the tool's purpose and the cost. It is front-loaded, contains no filler, and every word earns its place. This is an exemplary concise description.
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 an informational tool with no parameters and no output schema, the description is complete enough: it states what it does and the cost. It does not describe the content of the explanation, but that is not necessary for an agent to decide to call it. It covers the essential context.
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 tool has zero parameters, so the schema coverage is trivially 100%. Per the rubric, a baseline of 4 applies. The description adds no parameter information because none exist, which is appropriate and adds no confusion.
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 the tool explains a specific resource: AlpineLead's deterministic Motion + Causality shadow layer. The verb 'explain' and the resource name are unambiguous, and it is distinct from sibling tools by topic, though it does not explicitly name an alternative. It could be a 5 if it explicitly differentiated, but the purpose is solid.
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 implies the tool is for understanding the shadow layer, but it does not provide explicit when-to-use or when-not-to-use guidance, nor does it name alternative tools. Given the large sibling set, some usage context would help, but the purpose itself gives an implied usage scenario.
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.
Several tools overlap or duplicate: run_sales_mission intentionally duplicates check_sales_mission_status and get_sales_mission_result, and there are multiple capability/routing tools (get_capabilities, match_alpinelead_capability, get_alpinelead_recommendation_packet, recommend_next_tool) with similar purposes. Blank descriptions for several nexus_* tools make their boundaries even harder for an agent to determine.
All names use snake_case, but there is no consistent verb_noun pattern. The set mixes prefixed families (agentpub_*, nexus_*, predictive_*_info), noun-only names (winning_pattern, learning_engine), reversed noun_verb names (radar_check, hunter_run), and get/check/run/status variants for closely related operations.
56 tools is far beyond a well-scoped server surface. Many are one-off info, status, or diagnostic tools that could be consolidated into parameterized tools. This places an excessive routing burden on the agent and dilutes the core sales workflow.
The core lead-to-CRM workflow is fairly complete: discovery, analysis, qualification, sales kit generation, HubSpot push, and learning/feedback loops are covered. However, there are notable gaps such as no way to list or retrieve saved analyses, no explicit stop/cancel for Hunter or Sales Mission runs, and no update/cancel operations for Nexus tasks.