The $49 bulk legacy-file conversion: what it costs, what it can read, what happens when a file fails.
Give file_count and total_mib to have the limits checked against your job.
This never charges and never uploads — the authoritative per-file answer
comes from the FREE preflight, which sniffs the actual bytes.| Name | Required | Description | Default |
|---|---|---|---|
| total_mib | No | ||
| file_count | No |
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?
With no annotations, the description carries the full behavioral burden. It discloses important traits: no charge, no upload, and non-authoritative results. However, it promises to explain 'what happens when a file fails' but never actually explains it, and it omits any mention of required permissions or response characteristics.
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?
Three compact, front-loaded sentences: the offer and scope, the usage instruction, and the behavioral caveat with an alternative. Every sentence earns its place, and there is no redundant or filler wording.
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 simple tool with two defaulted parameters and no output schema, the description explains the purpose, safety, and primary alternative. But it never states what the tool returns or the exact limits being checked, leaving the agent to guess at the response shape. This is a notable gap given there is no output schema to fill it.
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?
Schema description coverage is 0%, so the description must compensate. It explicitly ties both parameters to their purpose: file_count and total_mib are used to check limits against the job. This adds meaning beyond the schema names and types. It doesn't explain default behaviors or constraints, which keeps it from a 5.
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 a specific resource: a $49 bulk legacy-file conversion offer, and its function: checking limits for a job based on file_count and total_mib. It distinguishes itself from the FREE preflight, making its scope clear. However, it lacks a single crisp verb like 'estimate' or 'quote', and the opening sentence is more of an agenda than a function statement.
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?
Explicitly says to provide file_count and total_mib for limit checks and contrasts itself with the authoritative FREE preflight. It also clarifies that this tool never charges or uploads, preventing misuse. It does not name the exact sibling tool for preflight, but the alternative is clearly referenced.
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.