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reservoir

One reservoir (e.g. lake-mead, elephant-butte): capacity basis, latest reading, series.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

B3.4/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only lists output categories and does not state whether the operation is read-only, how recent the latest reading is, what happens for an invalid slug, or any data-freshness details. This is thin for a tool with zero annotation coverage.

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 compact fragment with no filler. The core idea of 'one reservoir' is front-loaded, and the examples earn their place by clarifying the slug parameter.

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?

For a simple one-parameter lookup, the high-level output description is passable, but the absence of an output schema and annotations leaves gaps around units, series date range, and error behavior. An agent could invoke it correctly but would still have limited understanding of the full response.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema only provides a 'Slug' title with 0% description coverage. The description compensates by giving concrete example slugs (lake-mead, elephant-butte) and indicating that the slug selects one reservoir. It does not enumerate all valid slugs or specify formatting rules, but it adds meaningful value for the only required parameter.

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

Purpose4/5

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

The description identifies the resource as a single reservoir and lists what is returned: capacity basis, latest reading, and series. The singular 'One reservoir' distinguishes it from the sibling 'reservoirs' tool, though it lacks an explicit verb like 'get' or 'retrieve'.

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 phrasing 'One reservoir' implies this tool is for a specific reservoir rather than a list, and the examples hint at valid slugs. However, it does not explicitly name alternatives or state when not to use it, leaving usage guidance mostly implicit.

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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TDQS

B3.4/5.0
Disambiguation4/5

Most tools target clearly distinct resources or actions: reservoirs vs reservoir, superfund_summary vs superfund_site, and the various search tools are separated by domain. A few pairs could be confused at a glance—officer_lookup vs search_officers and meeting vs search_meetings—but their descriptions remove practical ambiguity.

Naming Consistency3/5

The naming is readable but mixes conventions: some tools use verb_search (search_meetings, search_officers), some use noun_noun (reservoir, superfund_site, trading_post_ledger), and others use a mix like officer_lookup and register_verify. There are consistent subgroups, but no overarching verb_noun pattern.

Tool Count4/5

At 19 tools, the server is on the heavier side, but the breadth of the platform—meetings, reservoirs, superfund sites, officers, legacy conversion, evidence packs, and trading post—justifies most of them. Each tool names a meaningful capability, and none feels redundant enough to cut outright.

Completeness4/5

The set covers the main read/query lifecycle for its data domains: listing, searching, fetching details, and summarizing. The largest gap is that paid conversions and evidence-pack results hand off to external HTTP endpoints or email rather than being fully queryable inside the MCP, but that appears intentional.

Resources