legacy_formats
The 64 legacy municipal file formats the converter identifies (WordPerfect, Lotus, dBASE, .msg, …).
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
The 64 legacy municipal file formats the converter identifies (WordPerfect, Lotus, dBASE, .msg, …).
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
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 characterizes the data ('the 64 legacy municipal file formats') rather than the tool's behavior, and does not state that the tool returns the list, is read-only, or has no side effects. This is acceptable for a simple constant but still lacks explicit behavioral transparency.
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 with no filler; it states the count, domain, and representative examples. The word order is slightly awkward, but every element earns its place.
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?
For a zero-parameter, no-output-schema tool, the description is mostly sufficient, but it does not explicitly state what calling the tool returns. The agent can infer it yields the list of formats, yet a clearer 'returns X' statement would close the gap.
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 tool has zero parameters and an empty schema, so there are no parameter semantics to document. Per the zero-parameter baseline, this is adequate; 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.
Does the description clearly state what the tool does and how it differs from similar tools?
The description identifies the tool's resource: the fixed set of 64 legacy municipal file formats, with examples such as WordPerfect, Lotus, dBASE, and .msg. It is not a tautology and is clear, but it lacks an explicit action verb such as 'lists' or 'returns,' so it stops short of a 5.
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?
The description offers no guidance on when to use this tool or how it relates to alternatives. It does not mention any exclusionary conditions or sibling tools, leaving the agent to infer usage from the name and noun phrase.
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.
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.
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.
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.
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.