Skip to main content
Glama

get_event_detail

Summary stats for one market price event by id (per-interval dispatch during the event is not exposed).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesEvent id

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It adds one valuable limitation ('per-interval dispatch during the event is not exposed') which clarifies what data is unavailable. However, it does not mention what 'summary stats' includes or the nature of the return value, leaving moderate gaps.

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 a single sentence, front-loaded with the core purpose, and includes a parenthetical caveat. Every word earns its place, with no redundancy or filler.

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?

The tool is simple (one parameter, no output schema), but the description does not fully explain what response to expect beyond 'summary stats'. The added caveat about per-interval dispatch is useful, but the lack of detail about the output format leaves the description somewhat incomplete for an agent expecting precise return values.

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 coverage is 100%, and the single parameter 'id' is already described as 'Event id'. The description adds no additional meaning about the parameter format or source, so it relies on the schema. This meets the baseline of 3.

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

Purpose5/5

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

The description 'Summary stats for one market price event by id' clearly identifies the specific verb (get), resource (market price event), and scope (summary stats, by id). It distinguishes itself from sibling tools like list_events (which lists events) and battery-related tools, making the purpose unmistakable.

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

Usage Guidelines3/5

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

The description implies usage when you need summary stats for a single event and already have an id. It does not explicitly mention alternatives or when not to use it, but the 'by id' wording and sibling tool names (e.g., list_events) provide enough contextual guidance.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.2/5.0
Disambiguation4/5

Most tools are cleanly separated by object and action, but get_battery_detail, get_battery_revenue, and get_battery_optimal all overlap around battery revenue metrics and depend heavily on long cross-references and warnings to prevent misuse. The descriptions help considerably, but there are still realistic misselection paths.

Naming Consistency5/5

All tool names follow snake_case verb_noun patterns, using get_ for metrics/details and list_ for enumerations, with query_ for the natural-language endpoint. Minor vocabulary differences such as BESS versus battery do not undermine the overall consistency.

Tool Count5/5

Eight tools is comfortably within the well-scoped range and each tool covers a distinct analytical surface: inventory, fleet summary, battery revenue, optimal dispatch, events, and natural-language querying. The set feels intentionally assembled rather than padded.

Completeness4/5

The server covers battery inventory, event access, fleet-level context, per-battery revenue, optimal-dispatch benchmarking, and a general query interface, which is strong for a read-only analytics domain. The main gaps are lack of per-interval event dispatch data and the explicit unqueryability of the market-* cache tables.

Resources