trinity-research

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

With no annotations, the description carries full responsibility. It explicitly states 'Judges only from retrieved sources — never fabricates' and defines the semantics of 'contradicted' vs 'unverified', which are crucial behavioral traits.

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 compact and front-loaded: purpose in the first sentence, output structure in the second, and semantic clarifications in the remainder. Every sentence adds value without padding.

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 no output schema, the description thoroughly explains the return object (verdict, score, reasoning, sources) and defines the judgment criteria. It also covers the absence-of-evidence case, making it complete for an agent to understand expected behavior.

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 description doesn't need to add parameter details. It does not explain the 'count' parameter's range, but the schema already documents it (albeit with an internal inconsistency between max=255 and description max=10).

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 a specific verb and resource: 'Verify a factual claim against multiple live web sources (Brave).' It clearly distinguishes itself from siblings like ping or structured_brief_synthesizer by focusing on verification with a defined output structure.

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 the tool: when a factual claim needs to be checked against live sources. It does not explicitly name alternatives or conditions for not using it, but the purpose is 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?

With no annotations provided, the description carries the disclosure burden. It accurately describes the return value and echoes behavior. It does not mention side effects, but for a read-only liveness check this is adequate.

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 concise sentences convey all necessary information with zero redundant text, perfectly front-loaded and 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?

For a one-parameter utility with no output schema and no annotations, the description adequately conveys purpose, behavior, and parameter usage. It could mention error handling or lack of side effects, but these are not essential for a liveness probe.

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 fully documents the optional message parameter with a clear description ('Optional message echoed back'). The tool description adds no new semantic meaning beyond confirming the echo, so a baseline 3 is appropriate per high schema coverage.

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 as a 'Liveness probe' and specifies the output ('Returns pong plus any supplied message'). This specific verb+resource distinguishes it from the unrelated sibling tools.

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 liveness probe purpose clearly implies when to use it (e.g., connectivity checks), though it does not explicitly name alternatives or exclusions. Since no sibling tools are similar, the context is sufficient.

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 the return format (masked text plus a redaction count by type) and the scope of PII detection, which adds behavioral context beyond the schema. However, with no annotations provided, it carries the full burden and does not explicitly mention data handling, limitations, or whether the operation is read-only.

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 every word earning its place. It leads with the action verb, specifies the return value, and adds a relevant use-case context. 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 tool with a single parameter, the description covers purpose, operation, and return type, which is quite complete. The only minor gap is the exact masking format (e.g., '[REDACTED]'), but this is not critical for understanding 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?

The input schema covers the only parameter 'text' completely, giving a baseline of 3. The description enriches this by enumerating the types of PII detected (emails, phone numbers, IDs, names), helping the user understand what content is relevant for redaction.

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 a specific verb 'Redact' with a clear resource 'personally identifiable information (PII)' and gives concrete examples (emails, phone numbers, IDs, names). This distinguishes it from sibling tools like multi_source_validator and structured_brief_synthesizer, which focus on validation and synthesis respectively.

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 phrase 'Privacy-by-default for research workflows' provides some context about when to use the tool, but it does not explicitly compare with alternatives or state when not to use it. No exclusions or alternative tool names are mentioned.

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 of behavioral disclosure. It adds valuable behavioral context by stating that citations are inline as [n] and that facts are never invented beyond the sources. This goes beyond the basic schema information, though it does not discuss potential edge cases or error handling.

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 and front-loaded with the main purpose. It uses a single sentence with a colon to list the optional formats, followed by two short behavioral notes. Every word adds value, with no redundant or filler content.

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 two parameters and no output schema, the description provides sufficient context. It explains the input, output formats, citation style, and fact fidelity. It does not explain what happens with conflicting sources or how citations are numbered, but these are not critical for selecting and invoking the tool 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?

The input schema already provides full descriptions for both parameters (format and sources), covering 100% of parameter semantics. The description adds a little extra context by explaining the format options and emphasizing source fidelity, but it mostly restates what the schema already documents, 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: synthesizing multiple sources into a structured, cited brief. It names the specific output formats and explicitly mentions that it cites inline as [n], distinguishing it from sibling tools like multi_source_validator or privacy_shield_redact.

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 the tool (when you need to synthesize sources into a brief) and provides format options, but it does not explicitly state when not to use it or mention alternatives. There is no exclusionary guidance relative to sibling tools, so the usage context is implied rather than explicit.

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