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

Annotations already declare readOnlyHint=true, indicating no destructive behavior. The description adds 'full contradiction check' but does not elaborate on behaviors such as computational intensity or dependencies. With annotations covering the safety profile, the description provides limited additional transparency.

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, no filler. The first sentence states purpose, the second adds critical input format. Every word 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?

Given the tool's low complexity (2 simple string params) and the presence of an output schema, the description adequately covers the functionality. It mentions vault inference, which is essential for context. Minor omission: no hint about what the check returns, but the output schema likely handles that.

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?

With 0% schema description coverage, the description fills the gap by clarifying that parameters accept 'absolute paths or filename stems', adding meaning beyond the parameter names and string types in the schema. It applies to both parameters and is directly useful.

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 specifies the action ('Run the full contradiction check') and the resource ('between two specific notes'), clearly distinguishing from sibling tools like find_contradictions which likely operates more broadly. However, it does not explicitly contrast with siblings.

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 input format guidance ('absolute paths or filename stems within a vault that can be inferred'), which implies usage context, but it lacks explicit when-to-use or when-not-to-use instructions relative to siblings like extract_claims or generate_reconciliation_prompt.

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 adds context about extracting claims and negation patterns, and mentions structured output. Annotations already indicate readOnlyHint=true, so no contradiction. It does not disclose other behavioral aspects like auth needs or rate limits.

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 sentence with minimal waste. The '[Pro]' prefix may be extraneous but does not significantly impact conciseness. It is front-loaded with the core action.

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 one parameter and an output schema, so the description can focus on purpose. It explains the extraction content but omits explanation of the note_path parameter. Given the low parameter count, it is adequate but not fully 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 has 0% description coverage, meaning the description does not explain the 'note_path' parameter. The tool name and description imply a single note, but no additional meaning is provided for the parameter beyond what the schema indicates.

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 extracts quantitative claims and negation patterns from a single note, using specific verbs like 'Pull' and specifying the resource. However, it does not differentiate explicitly from sibling tools like 'find_contradictions' or 'check_pair'.

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 guidance is provided on when to use this tool versus alternatives. The description does not mention prerequisites, exclusions, or alternative 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?

The description adds no behavioral context beyond what annotations provide (readOnlyHint=true). It does not contradict annotations, but also does not disclose additional traits such as performance expectations or data requirements.

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, concise sentence with no redundant or irrelevant information. It efficiently conveys the core purpose.

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 presence of an output schema and the tool's search nature, the description is somewhat complete. However, it lacks details about performance, edge cases, or required vault_path properties, making it merely 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?

With 0% schema description coverage, the description should compensate by detailing parameter meanings, but it only mentions vault_path implicitly. Parameters like limit and min_shared_concepts are not explained, though their names are somewhat self-explanatory.

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 scans the vault for note pairs with high concept overlap and conflicting claims. It uses specific verb 'scan' and identifies the resource and outcome, distinguishing it from siblings like check_pair and extract_claims.

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 no explicit guidance on when to use this tool versus alternatives. While sibling names hint at different use cases, the description itself lacks context about when to prefer find_contradictions over check_pair or extract_claims.

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 annotation readOnlyHint:true already informs the agent that this is a safe, non-mutating operation. The description adds that it 'produce[s] a structured LLM-ready prompt,' clarifying the output type but does not disclose other behavioral traits such as whether it requires specific permissions, handles errors from missing notes, or has any side effects. Given the annotation covers the safety aspect, the description adds moderate value.

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 sentence that is front-loaded with a clear verb and resource. It contains no unnecessary words and effectively communicates the tool's purpose. Every part earns its place, making it concise and well-structured.

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 has 2 parameters, a read-only annotation, an output schema, and siblings, the description is incomplete. It does not describe the parameters' formats or expected values, nor does it explain what the 'LLM-ready prompt' looks like (though the output schema might cover that). The agent lacks sufficient context to confidently invoke the tool without additional assumptions.

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 mentions 'two notes' and uses note_a_path and note_b_path, implying these are paths to notes. However, it does not elaborate on the format, constraints, or examples of valid paths. The high-level context is provided, but deeper detail is absent, limiting the agent's ability to construct correct inputs.

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 purpose: 'produce a structured LLM-ready prompt for reasoning through the conflict and suggesting resolution.' The verb 'produce' and the resource 'structured LLM-ready prompt' are specific. It distinguishes from siblings such as 'find_contradictions' and 'check_pair' by focusing on generating a reasoning prompt rather than detecting or checking contradictions.

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 usage context with 'For a detected contradiction between two notes,' indicating it should be used after a contradiction is found. However, it does not explicitly state when to use it versus alternatives like 'extract_claims' or 'check_pair,' nor does it provide any exclusions or warnings. More explicit guidance would improve decision-making.

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