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trading_post_ledger

The public sales ledger — totals only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

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

  1. First observed

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 behavioral burden. 'Public' indicates accessibility and 'totals only' discloses that itemized transaction details are not returned, which are useful constraints. However, it omits details like response format, data freshness, or any rate limiting.

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 extremely compact and front-loaded. Every word contributes meaning: 'public' gives access scope, 'sales ledger' identifies the resource, and 'totals only' sets output expectations.

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

Completeness4/5

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

For a zero-parameter, simple read-oriented tool, the description covers the essential points: what resource is involved and what kind of data to expect. It does not specify formatting or exact return fields, but 'totals only' gives enough orientation for an agent to invoke it appropriately.

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 tool has zero parameters, so the baseline is 4 per the rubric. There is no parameter documentation burden, and the description does not need to compensate for schema gaps.

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 clearly identifies the resource as the public sales ledger and adds the scope 'totals only,' which distinguishes it from catalog-like siblings. It lacks an explicit verb such as 'retrieve' or 'return,' so it stops short of a perfect 5.

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 phrase 'sales ledger — totals only' implies this tool is for aggregated sales data, but there is no explicit statement of when to use it over alternatives. None of the sibling tools are mentioned, and no when-not-to-use guidance is provided.

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.

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