Cross-references for a verse (OpenBible.info, ranked by community votes), with the target text included. E.g. reference='Romans 5:12'.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| reference | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
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 burden. It discloses that results are ranked by community votes and includes target text, which is useful. However, it doesn't describe behaviors like whether the ranking is ascending/descending, rate limits, or data freshness. It's read-only in nature but doesn't explicitly state so.
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 two sentences with a concrete example. It packs source, ranking, and output content into the first sentence. The example is well-placed. Minor waste: the example could be considered redundant with the reference parameter, but it adds concrete grounding. No excess text.
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 tool has an output schema, so return-value documentation is covered structurally. With 2 parameters and one explained via example, the description covers the core use case. Given the tool's moderate complexity, the description is reasonably complete, though the limit parameter semantics could be more explicit.
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 0%, so the description must compensate. It explains the 'reference' parameter through the example 'Romans 5:12' and the target text behavior. However, the 'limit' parameter (default 20) is entirely unexplained in the description, leaving the agent unsure of its meaning without schema explanation.
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 clearly states verb+resource: 'Cross-references for a verse (OpenBible.info, ranked by community votes), with the target text included.' It names the data source, ranking mechanism, and includes an example query. This distinguishes it from siblings like get_citations, find_similar, and word_study.
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 provides an example usage (reference='Romans 5:12') which implies the query format, but does not explicitly state when to use this tool versus alternatives like get_citations or find_similar. Usage context is implied but not explicit.
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 targets a distinct function: text retrieval, interlinear, word study, cross-refs, citations, entities, search, similarity, reading works, and corpus info. Even search, semantic_search, and find_similar are clearly differentiated by input type (keyword, theme, passage reference) and purpose.
The set mixes verb-prefixed names like get_passage and read_work with noun-style names like corpus_info and word_study, plus bare verbs like search. All use snake_case, but the lack of a uniform prefix or consistent verb-noun pattern reduces predictability.
13 tools is well within the ideal range for a specialized study server. Each tool addresses a distinct research need, from scripture retrieval to original-language analysis, without redundancy or bloat.
The surface covers the full biblical research workflow: text retrieval, comparison, interlinear, word study, cross-references, patristic citations, entities, multiple search modes, and reading related prose works. Search and semantic_search fill discovery gaps, and corpus_info provides structural orientation.