bible-copilot

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

No annotations are provided, so the description carries the full burden. It discloses the core behavior (existence check and URL retrieval) and implies a read-only operation, but it does not specify what happens when no study page exists (e.g., returns null, false, or an error).

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, front-loaded sentence that conveys the tool's purpose without redundancy. Every part of the sentence contributes useful 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?

For a tool with one simple parameter and no output schema, the description adequately conveys what the tool does. Minor omission: it doesn't clarify the return behavior when the study page does not exist, but overall the tool is simple enough that the description is nearly 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?

The schema covers the single 'passage' parameter with a clear description and example. The tool description adds no additional parameter meaning beyond what the schema already provides, so a 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 a specific action: checking whether a free in-depth study page exists for a Bible verse on a named site, and getting its URL. This distinguishes it from sibling tools like get_verse_text (text retrieval) or resolve_reference (reference resolution).

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?

No explicit guidance is given on when to use this tool versus alternatives. It implies use for checking existence/URL of a study page, but it doesn't mention alternatives, exclusions, or relevant context such as needing a valid passage reference.

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?

With no annotations provided, the description carries the full burden. It discloses key behavioral traits: the tool is deterministic (no AI generation), returns exact text, and uses public-domain translations. This is valuable context for an agent deciding between this and study tools. It could mention error handling or return formatting, but for a simple retrieval tool, the transparency is above average.

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 sentences, front-loaded with purpose, followed by a key behavioral trait. Every word earns its place; no fluff or repetition. Excellent conciseness.

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 simple (2 parameters, no output schema). The description covers purpose, input granularity (verse/passage/chapter), translation option, and deterministic behavior. Given the low complexity, this is fully complete for an agent to select and invoke it correctly.

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. Both parameters (reference and translation) are described in the schema. The description adds minor context by explaining 'kjv = King James Version', which aids understanding of the enum, but it does not significantly add meaning beyond the schema. Baseline 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: fetching exact text of Bible verses, passages, or chapters. It specifies the resource (text) and the source (public-domain translation), and distinguishes it from sibling tools like 'find_verse_study_page' or 'study_bible_passage' by focusing on raw text retrieval.

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 implies when to use this tool: when you need exact, deterministic text from a public-domain translation. It does not explicitly name alternatives or exclusions, but the deterministic/no-AI-generation note helps differentiate it from study or verification tools. Clear context, though no explicit alternative comparison is given.

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?

No annotations are provided, so the description carries full burden. It discloses 'Deterministic — no AI generation' and lists output fields, but doesn't mention error handling, network dependence, or permission requirements. Some behavioral context is provided, but gaps remain.

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, front-loads the purpose, uses concrete examples, and includes return values and determinism note. Every sentence contributes value.

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 tool with no output schema and no annotations, the description explains return fields and determinism, but lacks explicit disambiguation from siblings and error behavior. Given the moderate complexity, it is mostly 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?

The input schema already describes both parameters with examples, and the description repeats similar info. Schema coverage is 100%, so the description adds no significant extra meaning 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 uses the specific verb 'normalize' with resource 'Bible reference', states it returns canonical form, and contrasts with siblings like get_verse_text by focusing on reference resolution rather than text retrieval.

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 implies usage for converting arbitrary user references to canonical form, but does not explicitly name alternatives or state when not to use it. The context is clear, but no exclusions or sibling comparisons are provided.

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?

With no annotations, the description carries the full burden. It explicitly discloses that answers are AI-generated and advises verifying quotes before publishing, which is critical behavioral information. It also explains each study mode, though it does not discuss response length or other potential limitations beyond the AI-generated warning.

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, front-loaded with purpose, then mode explanations and a verification warning. Every sentence earns its place with no redundancy or filler.

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 moderate-complexity tool with full schema coverage and no output schema, the description is mostly complete. It covers the core behavior, mode semantics, and the critical AI-generated caveat. However, it does not describe the expected response format or length, which would be slightly helpful though not essential.

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 has 100% parameter coverage with descriptions for passage, mode, and question. The description adds meaningful context by defining what each mode does (e.g., 'summary', 'observe', 'interpret'), going beyond the enum names. It does not need to restate passage/question since the schema covers them.

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 answers questions about Bible passages with Scripture-cited answers, and it lists six specific study modes. This distinguishes it from siblings like get_verse_text (raw text retrieval) and verify_scripture_quote (verification) by emphasizing AI-generated study and Q&A.

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 gives clear usage context ('Ask any question about any Bible verse or passage') and explicitly recommends verify_scripture_quote when publishing, providing an alternative for verification. It does not explicitly exclude siblings like get_verse_text, but the study-vs-text distinction is implied.

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?

With no annotations provided, the description takes full responsibility for behavioral disclosure. It discloses return values ('whether the quote is real, the exact canonical wording, the correct reference, and a confidence score') and a key behavioral trait ('Deterministic — no AI generation'). This goes beyond typical tool descriptions and sets clear expectations.

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 three sentences: the first clearly states the purpose, the second lists return values, and the third provides usage guidance and a determinism note. Every sentence carries weight, with no redundant information, making it concise and front-loaded.

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?

Although there is no output schema, the description fully covers what the tool returns, including the confidence score. It also specifies the use case and deterministic nature, making the description complete for this simple verification tool with only one required parameter.

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 meaningful detail beyond the schema; it refers to 'claimed Bible quote' and 'correct reference,' but the schema already describes the quote and reference parameters fully. Thus, the description adds no extra semantic value for parameters.

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: 'Fact-check a claimed Bible quote against the actual text.' It specifies the verb 'fact-check' and the resource 'Bible quote,' and further distinguishes itself from siblings by detailing that it returns verification results, exact wording, reference, and confidence score.

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 explicit usage context: 'Use this before publishing any Bible quote to catch misquotes, wrong verse numbers, and verses that do not exist in the Bible at all.' This clearly indicates when to use the tool, though it does not explicitly mention alternatives or when not to use it.

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