Get lines from one collection by its URL. Each line comes with a literal English gloss.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| register | No | Optional filter: flirty, romantic, funny… | |
| collection | Yes | Collection URL, e.g. /tl/lines/tagalog/ |
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 provided, the description carries the full behavioral burden. It usefully reveals that results include a 'literal English gloss', but it does not disclose ordering, determinism, error behavior, pagination, or the full response shape. This is adequate for a simple read operation but incomplete without annotation support.
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?
Two short, focused sentences with no filler. The primary action is front-loaded, and the gloss detail is a valuable second sentence. Every phrase 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?
The description plus schema is mostly enough to call the tool correctly: required collection URL, optional limit and register, and output content are all represented. Without an output schema or annotations, a bit more detail about return shape or ordering would make it fully complete, but the gap is minor for a simple collection-listing tool.
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 coverage is 67%, with collection and register already documented in the schema. The description reinforces the collection-URL concept but adds no extra meaning for limit or register beyond what the schema's types, defaults, ranges, and descriptions already provide.
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 states a specific action ('Get lines') and a specific resource ('from one collection by its URL'), plus a non-obvious output trait: each line comes with a literal English gloss. This distinguishes it from siblings like search_lines and random_line, which imply different selection mechanisms.
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 conveys the core usage context: use this tool when you already know a specific collection URL and want its lines, rather than searching or picking randomly. It does not explicitly name alternatives or state when not to use it, so it misses the top level of guidance.
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.
Each tool serves a distinct purpose: listing collections, retrieving all lines from a collection, getting a random line, and searching lines. No two tools appear to do the same thing, and the descriptions make the boundaries clear.
Three tools follow a clear verb_noun pattern (get_lines, list_collections, search_lines), but random_line is an adjective_noun exception. Overall the naming is predictable and readable, with only a minor deviation.
Four tools is well-scoped for a read-only pick-up line server. Each tool earns its place and there is no bloat or noticeable thinness.
The server covers the core read workflows: discover collections, fetch lines from a collection, get a random line, and search across all lines. There are no obvious missing operations for the stated domain.
