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 the use of a DummyEmbeddingFunction when no model is given, which is a key behavior. However, it does not mention whether the tool is read-only, side effects, or other important 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 a single sentence, concise and front-loaded. It could be more structured (e.g., listing modes separately), but it is not unnecessarily verbose.

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 8 parameters, no output schema, and no parameter descriptions, the description is far too minimal. It fails to explain return values, how results are presented, or how parameters interrelate, making it incomplete for effective use.

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%—all 8 parameters have only titles. The description adds no explanation of any parameter, leaving their meaning entirely to the schema with no additional context.

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 can perform a dry-run cost estimate or a full evaluation, and mentions using a DummyEmbeddingFunction if no model is provided. This differentiates it from siblings like list_strategies and preview_chunks.

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 each mode (dry_run vs full evaluation), but provides no explicit guidance on when to choose this tool over its siblings. No exclusions or alternatives 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 does not state that the tool is read-only (safe), nor does it mention any side effects, authentication requirements, or rate limits. The agent can infer that listing is non-destructive, but this is not explicit.

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, well-structured sentence of 10 words. It is front-loaded with the action and resource, and every word contributes meaning. There is no fluff or 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 simplicity of the tool (one optional parameter, output schema exists), the description provides the essential functionality. However, it lacks context about what 'chunking strategies' are and how they are registered. For a standalone tool, this might be insufficient without additional documentation.

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 description adds minimal value beyond the input schema. It merely paraphrases 'optionally filtered by content type', which mirrors the schema property. Since schema description coverage is 0%, the description should compensate with more detail (e.g., allowed values, behavior when null), but it does not.

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 action ('List'), the resource ('registered chunking strategies'), and includes a filtering condition ('optionally filtered by content type'). It effectively differentiates from sibling tools like evaluate_chunking, preview_chunks, and recommend_config by focusing on listing rather than evaluation, preview, or recommendation.

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 its siblings. There are no 'when-to-use' or 'when-not-to-use' statements, and no mention of alternatives. The agent is left to infer usage context from the tool name alone.

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 must bear the full burden. It implies no embeddings and inline processing, but does not explicitly state that no data is persisted or that the operation is idempotent. The output schema exists but behavioral side effects are not addressed.

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, very concise. However, it sacrifices useful details that could be added without becoming verbose, such as examples or config structure.

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 three parameters, zero schema descriptions, and a sibling set, the description is insufficient. While the output schema covers return values, the lack of parameter guidance and usage context makes it incomplete for an AI agent to use 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 description coverage is 0%. The description only hints that 'strategy_name' selects a strategy and 'config' holds parameters, but does not explain the format or constraints for 'config' (anyOf object/null). No enum values or examples are provided.

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 action ('chunk'), the resource ('inline text'), and includes a distinguishing detail ('no embeddings'). However, it could better differentiate from sibling tool 'evaluate_chunking' which likely involves evaluation.

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 given on when to use this tool versus siblings like 'evaluate_chunking', 'list_strategies', or 'recommend_config'. The description does not specify prerequisites or contexts.

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 must carry the full burden. It discloses the use of dummy embeddings by default, but does not mention side effects, idempotency, or other behavioral traits like whether it modifies state or runs asynchronously.

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 extremely concise at one sentence, but at the cost of missing critical information. It is structured well enough for a simple statement, but could be expanded to include essential details without becoming verbose.

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 7 parameters, no output schema, and no annotations, the description is severely incomplete. An agent cannot determine what the tool returns, how to set parameters correctly, or what the expected behavior is beyond a vague 'tuner' operation.

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 explain parameters. It does not mention path, top_k, max_docs, use_case, strategies, content_type, or embedding_model, leaving all semantics to be inferred from parameter names alone.

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 says 'Run tuner and return ranked Recommendation', which vaguely states a tuning action but does not define what a 'tuner' or 'Recommendation' is in this context. The phrase 'uses dummy embeddings by default' adds some specificity but the core purpose remains unclear.

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 on when to use this tool versus its siblings (evaluate_chunking, list_strategies, preview_chunks). The description does not mention alternatives or conditions for use, leaving the agent to infer.

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