installed_capacityYear-end installed generation capacity by production type (MW).
| Name | Required | Description | Default |
|---|---|---|---|
| area | Yes | Bidding-zone EIC code | |
| year | Yes | Year (e.g. 2024) |
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Query parameters sent to ENTSO-E API | |
| time_series | Yes | Array of installed capacity time series by type | |
| time_series_count | Yes | Number of time series returned |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, covering safety traits. The description adds no further behavioral context (e.g., data freshness, aggregation level). With annotations present, the bar is lower, but the description adds minimal value beyond what annotations and schema provide.
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 conveys the core purpose. It contains no unnecessary words and is efficiently front-loaded with the key information.
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?
Given the tool's simplicity (2 params, output schema exists), the description is mostly sufficient. It mentions the key output dimension 'by production type'. However, it could briefly note that results are per the specified area and year, which is implied but not explicit.
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 100% of parameters with descriptions ('area' as bidding-zone EIC code, 'year' as numeric year). The description does not add any additional meaning beyond the schema, so baseline of 3 is appropriate.
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 returns 'year-end installed generation capacity by production type (MW).' It identifies the specific verb ('installed capacity') and resource ('by production type'), but does not distinguish it from the sibling tool 'actual_generation_per_type', which also involves generation capacity.
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?
There is no guidance on when to use this tool versus alternatives like 'actual_generation_per_type'. The description lacks any context about when to use this tool or when not to, and no alternatives are mentioned.
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.
The ENTSO-E energy tools are clearly distinct, but the Pipeworx half contains overlapping query modes: ask_pipeworx and ask_pipeworx_beta are explicitly identical right now, and ask_pipeworx/ask_pipeworx_grounded/deep_research/validate_claim all route natural-language questions to the same underlying catalog. The Polymarket tools also blur edge detection, arbitrage, fill-risk, and persistence tracking, so an agent can easily select the wrong one.
The five ENTSO-E tools use a clean snake_case noun pattern, but the rest mix brand verbs (ask_pipeworx, bet_research), bare memory verbs (remember, recall, forget), and polymorphic prefixes (polymarket_*), with inconsistent suffixes like beta, grounded, and kalshi_spread. There is no server-wide predictable naming convention.
36 tools is too many for the apparent scope, and the server name promises ENTSO-E while only 5 of 36 tools serve that domain. Even viewed as a general data utility, the count is heavy and includes duplicate query modes, though individual clusters do have some purpose.
For an ENTSO-E server, the five energy tools cover the basics (generation, load, price, flow, capacity) but omit common datasets like generation forecasts, balancing/imbalance prices, and outages. The unrelated Pipeworx tools add broad research, memory, and subscription coverage, but the overall surface feels like a general-purpose assistant with an energy add-on rather than a complete energy domain.