Bibelstudium MCP

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description adds substantial behavioral context beyond the readOnlyHint annotation: accentuation/case are ignored, reported differences are real variants or spelling variants (e.g., movable Ny), and it reports per-word attestation across eight editions. It also discloses the OT limitation. This exceeds what annotations alone convey.

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 front-loaded with the core action, followed by technical nuances, usage examples, and limitations. Every sentence earns its place, with no repetitive or filler content, and the length is appropriate for the tool's complexity.

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 comparison tool with an output schema, the description covers the essential aspects: what is compared, how differences are normalized, the attestation feature, and the OT limitation. The output format is presumably handled by the output schema, so no gaps remain.

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 input schema already provides full descriptions for all three parameters (100% coverage), including the German NT book naming convention. The description adds no additional parameter-specific semantics beyond the schema, so the baseline of 3 is appropriate.

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 the tool's function: 'Compare one NT verse word-by-word across the Greek editions... and list the textual differences.' This specific verb+resource distinguishes it from siblings like bible_lookup or bible_search, and the mention of per-word attestation further clarifies the scope.

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?

Explicit usage guidance is provided: 'Use for questions about textual variants (e.g. the Comma Johanneum, 1Jn 5:7).' It also gives a clear exclusion: 'OT verses have only one edition (WLC) and cannot be compared.' This tells the agent exactly when to select this tool over alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already include readOnlyHint=true, but the description adds substantial behavioral detail: it lists the exact outputs (total count, per-book distribution, occurrence list with inflected forms, lexicon data including Abbott-Smith for Greek) and explains NT edition selection via texttyp. It also clarifies that counts are always exact, which is useful behavioral information.

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 dense paragraph with no wasted words. It front-loads the purpose, then covers search methods, outputs, and edition selection. Every sentence adds critical information.

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 is complex, but the description covers the core functionality well: how to search, what results look like, and edition selection. Given an output schema exists, it doesn't need to detail return values. It's slightly incomplete around edge cases like mixed-testament searches, but overall it's adequate.

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 100% and each parameter is well-explained. The description adds value by marking Strong's as the preferred method and referencing bible_original, which provides additional context beyond the schema. It also explicitly notes the texttyp default and that it's ignored for Hebrew, though this is already in the schema.

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 opens with 'Concordance / word study: find ALL occurrences of an original-language word across the Bible.' This clearly identifies the tool's function (find all occurrences) and its scope (original-language words in the Bible). It distinguishes itself from siblings like bible_lookup or bible_search by focusing on word study and referencing bible_original for lemma input.

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?

It states when to use this tool ('word study') and gives specific search methods (by Strong's number or exact lemma from bible_original). It doesn't explicitly state when not to use it, but the context is clear enough to guide selection among the sibling tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the readOnlyHint annotation, the description adds useful behavioral details: ranking by relevance votes, inclusion of German text, a special caveat about editions that cap quoting (later targets carry only stelle and votes), and data sources. These go beyond what annotations provide.

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 concise (two sentences) and front-loaded with the core action. It efficiently packs important details like ranking, text language, and data source without redundancy.

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?

Given the output schema exists and parameters are well-documented, the description supplies the missing essentials: use case, data provenance, and a subtle behavioral nuance about target fields. It is complete for an agent to decide when and how to invoke the 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 description coverage is 100%, so the baseline is 3. The description does not add significant parameter-specific meaning beyond the schema; it only hints at the output structure, not the parameters themselves.

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 the tool finds cross-references (related/parallel passages) for one Bible verse, ranked by relevance votes, with German text. It differentiates from sibling tools by specifying the cross-reference use case and the output characteristics.

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?

It provides a clear use case: 'Use this to find where a theme, quote or promise recurs elsewhere in Scripture.' However, it does not explicitly name alternatives or when not to use this tool, so it lacks exclusion criteria.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the readOnlyHint annotation, the description discloses additional behavioral traits: footnotes are returned in the 'fussnoten' field with provenance, truncation can occur with `hinweis` and `gekuerzt`, and error responses name the nearest known book and canon coverage. This goes well beyond annotations.

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 front-loads the core purpose and then adds high-value usage rules and edge-case handling. While slightly verbose, every sentence earns its place—no filler or repetition. It could be tightened slightly, but it remains efficient.

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?

Given the tool's moderate complexity, the description covers footnotes, truncation, error behavior, canon questions, and memory-safety. With a rich output schema and readOnly/openWorld annotations, the description fully equips an agent to use the tool appropriately across normal and edge-case scenarios.

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 100% and all parameters have detailed descriptions, so the schema carries the heavy lifting. The description adds minimal param-specific value beyond referencing the default translation and hinting that translation availability is instance-dependent, but this does not materially enhance the schema's meaning.

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 opens with a specific verb and resource: 'Look up Bible verses by reference.' It clearly differentiates from sibling tools by stating it is for ALL Bible quotes and never to quote from memory, positioning it as the canonical lookup tool.

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?

Explicit when-to-use guidance is given: 'Use this for ALL Bible quotes — never quote from memory.' It also instructs to call the tool when a reference looks unfamiliar or before answering canon questions, and explicitly warns against skipping the tool for seemingly wrong references. This provides strong contextual usage direction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and openWorldHint=false, but the description adds substantial behavioral detail: coverage of the whole Bible, OT vs NT source texts, text-type options, the Comma Johanneum caveat, and the fact that output labels the edition. This goes well beyond the annotation baseline.

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 long but well-structured: purpose, use case, coverage, and text-type details are ordered logically. Every sentence contributes critical information, and the front-loaded opening gives immediate clarity.

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?

Given the tool's complexity (original language, morphology, OT/NT text types), the description covers all essential aspects: what is returned, how to choose text types, coverage scope, and output labeling. The presence of an output schema means return-value details are not required, and nothing important is missing.

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 100%, so the baseline is 3. The description adds significant meaning beyond the schema: it explains the OT/NT source difference, notes that texttyp is ignored for the OT, and highlights that 'tr' is the only text type with the Comma Johanneum, plus a comparison use case. This enriches parameter understanding usefully.

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 names a specific verb ('Return') and resource ('one Bible verse word-by-word in the ORIGINAL language with lemma, Strong's number and full morphology'), clearly differentiating it from translation-focused tools. The contrast with inferring from a translation reinforces a distinct purpose.

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 explicitly states when to use it ('verify what the original text says — e.g. whether a noun is singular or plural') and implicitly contrasts with translation-based inference. It does not name sibling tools but provides a clear use case and text-type selection guidance, making the intended context unambiguous.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description discloses rich behavioral traits beyond the readOnlyHint annotation: exact word matching, umlaut/accent folding ('fuhrt' matches 'führt'), phrase search, trailing-star prefix search, and optional book restriction. This gives the agent a thorough understanding of how the search behaves.

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?

Four sentences, each earning its place: purpose, syntax rules, use-case, and scope restriction. Information is front-loaded and free of redundancy. The structure flows naturally from what the tool does to how to use it.

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?

Given the tool's complexity (full-text search with syntax and translation options), the description covers key aspects: search semantics, use case, and book restriction. Output schema covers return values. A minor gap is the lack of mention of limit behavior or exclusions for sibling tools, but the description is largely complete.

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 100%, giving the baseline 3. The description adds significant meaning: query syntax examples (e.g., 'Hirte mangeln', '"Gnade um Gnade"'), wildcard semantics, and translation edition details including aliases and instance availability. This enriches parameter understanding beyond the schema.

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 opens with 'Full-text search over the German Bible text', a specific verb and resource that clearly defines the tool's function. It further details search features (exact word forms, phrases, prefix wildcard) which distinguishes it from sibling tools like bible_lookup or bible_compare.

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?

Explicit guidance is given: 'Use this to locate a passage when the wording is known but the reference is not.' This states the intended scenario clearly, but it does not mention alternative tools or exclusions, so it falls short of a full comparison with siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the readOnlyHint and openWorldHint annotations, the description discloses detailed output contents (edition licences, attributions, verbatim quote limits) and explicitly states it returns no scripture. This adds significant behavioral context without contradiction.

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 sentences, each with clear purpose: purpose, usage guidance, and disambiguation. No redundant words, front-loaded with the core function.

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 tool with an output schema, the description fully covers what the tool returns, when to use it, and how it differs from siblings. The mention of licensing and quote limits ensures the agent can plan longer quotations appropriately.

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, so the schema already communicates that. The description adds no parameter-specific syntax but focuses on output details, which is appropriate. Baseline per rules is 4 for zero-parameter tools.

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 the tool reports the server's release version and loaded Bible data with licensing and quote limits. It explicitly distinguishes from bible_lookup with 'Returns no scripture — use bible_lookup for verse text.'

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?

It specifies exact scenarios: 'when asked which version runs, when collecting facts for a bug report, and before planning a longer quotation.' Also gives an explicit alternative for scripture lookup, making usage boundary crystal clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.