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Get Dashboard Getpendingstatistics

hgr_get_dashboard_getpendingstatistics
Read-onlyIdempotent

Dedicated HGRApi tool for GET api/Dashboard/GetPendingStatistics. This is an explicit tool with a fixed endpoint; it is not a generic endpoint caller. HGRApi functional documentation: Purpose: Provides the GET get pending statistics operation in dashboard data. Use when: Use it when a client needs to run the get pending statistics operation for dashboard data. Input: Header channel: current ChannelOAuthId. Output: Returns the result or applies the effect of the get pending statistics operation. Search terms: dashboard getpendingstatistics. Requires HGRApi Header channel / ChannelOAuthId resolved internally.

Input Schema

NameRequiredDescriptionDefault
channelOAuthIdYesChannelOAuthId returned by hgr_list_channels for the selected visible store.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and non-destructive behavior, so the description does not need to carry the full safety burden. It adds that the endpoint is fixed and requires a ChannelOAuthId header, but otherwise uses generic language like 'returns the result or applies the effect' and omits rate limits, pagination, or data-scope details.

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

Conciseness3/5

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

The endpoint is front-loaded and the description is organized into purpose/use/input/output sections. However, it contains auto-documentation boilerplate, repeated phrases about being dedicated/explicit/not generic, and search terms that add little for an agent.

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

Completeness3/5

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

With one required parameter at full schema coverage, rich annotations, and an output schema, the description contains enough to invoke the tool. It is still incomplete for selection because it does not explain what pending statistics are or how this tool should be chosen over the other dashboard endpoints.

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%, so the schema already fully documents the sole channelOAuthId parameter. The description repeats that it is a header channel parameter but does not add meaningful semantics beyond the schema.

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

Purpose3/5

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

The description names the exact GET endpoint and says it returns dashboard pending statistics, but the purpose line mostly restates the tool name and endpoint. It does not explain what 'pending statistics' actually contain or differentiate this from the many other dashboard statistics siblings.

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 'Use when' section merely says to use it when a client needs to run the operation, which is tautological. It gives no alternatives, prerequisites beyond the header note, or exclusions versus sibling dashboard tools.

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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