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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, covering the safety profile. The description adds meaningful behavioral context beyond annotations: hybrid matching, tolerance to typos/variations, and the return shape. No contradiction with 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?

Three concise sentences with no filler. The main action is front-loaded, the use case is stated in the second sentence, and the output behavior is summarized in the third. Every sentence 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?

With no output schema, the description appropriately explains what the tool returns. It could have mentioned any dependency on a pre-built index or relationship to b_index_codebase, but that is inferable from the sibling set and is not a major gap for a two-parameter search 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 coverage is 100%, so the description does not need to re-document parameters. It adds value by explaining that the query can be natural language or specific terms and that semantic matching tolerates typos and variations, which directly informs how to set the query parameter.

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 states a specific verb and resource: 'Performs intelligent hybrid code search' on code, and clarifies the distinguishing mechanism ('semantic understanding with exact text matching'). It is immediately distinguishable from siblings like b_index_codebase and f_get_status. It also tells the agent what the tool returns: relevant code snippets with locations and line numbers.

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: use for finding code by meaning, even with typos or variations, with relevant natural language examples. It does not explicitly name alternatives or state when not to use this tool, so it falls just short of a 5.

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 the tool non-read-only, idempotent, and non-destructive. The description adds behavioral context by explaining that a reindex scans all files and updates the embeddings cache, which tells the agent what side effects to expect beyond the annotation flags.

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 no filler. The primary action is front-loaded ('Manually trigger a full reindex'), followed by the mechanism and a practical use case. Every sentence 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?

For a simple, one-optional-parameter tool with strong annotations and no output schema, the description is complete. It states the action, the effect, and when it is useful, which is sufficient for an agent to decide to 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?

The schema fully documents the single 'force' parameter with a clear description, so the description does not need to add much. The phrase 'full reindex' and 'even if files haven't changed' are consistent with the parameter, but the description itself does not add new semantic 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 opens with a specific verb and resource: 'Manually trigger a full reindex of the codebase.' It further clarifies the action by stating it will 'scan all files and update the embeddings cache,' making it clearly distinct from sibling tools like a_semantic_search or c_clear_cache.

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 clear context for when to use the tool: 'Useful after large code changes or if the index seems out of date.' It does not explicitly mention alternatives or when not to use it, but the guidance is specific enough to route an agent correctly.

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 behavioral detail beyond the annotations: clearing the cache 'forces a complete reindex on next search or manual index operation,' which helps the agent anticipate downstream effects. It does not contradict the destructiveHint or idempotentHint 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?

Two sentences with no filler: the action and consequence are front-loaded, and the usage context is given in one short clause. Every word contributes to understanding the tool.

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 destructive operation with clear annotations, the description covers what the tool does, what happens afterward, and when to use it. Nothing necessary for a correct invocation 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?

The tool has zero parameters and the schema description coverage is 100%, so there are no parameter details for the description to add. The baseline of 4 applies because there is nothing missing for an agent to invoke the tool correctly.

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 identifies the action ('clears') and the specific resource ('embeddings cache'), and explains the immediate consequence ('forcing a complete reindex'). This makes the tool's purpose unambiguous and distinct from siblings like a_semantic_search and b_index_codebase.

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 explicit when-to-use guidance: 'when encountering cache corruption or after major codebase changes.' It does not explicitly state when not to use the tool or name alternatives, but the stated use cases are clear enough for an agent to decide appropriately.

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 and idempotentHint, so safety is covered. The description adds that the return value is a version string and that lookups target official registries, which is valuable given the absence of an output schema.

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?

One front-loaded sentence with no filler. The long ecosystem list earns its place by defining the tool's scope and the package registries it supports.

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?

This is a simple read-only lookup tool. Annotations cover side effects, the schema covers all parameters, and the description states the return value, so an agent has what it needs to invoke 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?

Schema coverage is 100%, so both package and ecosystem parameters are already described in the schema, including the ecosystem enum. The description reinforces the supported ecosystems but does not add meaningfully 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?

States a specific action ('Get the latest version'), a clear object ('library/package'), and a source ('official registry'). This clearly distinguishes it from sibling tools like a_semantic_search and f_get_status, which serve unrelated purposes.

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 'help you avoid using outdated dependencies' gives a concrete use case for when to call this tool. It does not explicitly name alternatives, but the sibling tools are all unrelated in scope, so no exclusion is really needed.

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 the disclosure burden. It reveals a side effect not in the schema ('Creates cache folder automatically') and mentions optional re-indexing. However, it doesn't describe failure behavior, whether the old workspace index is preserved or removed, or whether re-indexing is synchronous; for a mutation with no annotation safety net, this is only moderate 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?

Three sentences, no filler, with the core action first, followed by usage guidance and side effects. Every sentence earns its place, and structure aids scanning.

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 description covers purpose, when to use, and key side effects, and the schema handles parameter meaning. It doesn't describe return values or error conditions, which is a gap given there's no output schema or annotations, but an agent has enough context to select and call it correctly in the common case.

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?

All three parameters are fully documented in the schema (100% coverage), so the baseline applies. The description adds no parameter-specific detail beyond what the schema already provides; it only restates the reindex concept in prose.

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?

States the exact operation ('Change the project workspace path at runtime'), naming both the action and the resource. It is clearly distinct from sibling tools such as a_semantic_search or c_clear_cache, which have different scopes.

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?

Gives an explicit trigger condition ('when you detect the current workspace is incorrect or you need to switch to a different project directory'), so an agent knows when to invoke it. It does not enumerate when-not-to-use cases or explicitly name alternative sibling tools, so it falls short of a full 5.

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. The verbs 'Get' and 'Returns' imply a read-only operation and the description lists the types of information returned, but it does not explicitly state that the tool has no side effects, requires no special permissions, or has any operational caveats.

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 no filler. It opens with the core purpose, then lists return categories, then adds a use case. Every sentence 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?

For a zero-parameter status tool without an output schema, the description does the necessary work by naming the return categories. It is adequate for an agent to know what the tool does and roughly what it returns, though it could be more explicit about the exact shape of the response or any operational caveats.

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, and the schema description coverage is 100%. Per the calibration baseline, no parameter documentation is needed, and the description's focus on return values 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 verb ('Get') and resource ('status information about the Smart Coding MCP server'), and enumerates the returned data: version, workspace path, model configuration, indexing status, and cache information. However, it does not explicitly distinguish itself from the sibling d_check_last_version, which also appears version-related, so it misses the strongest form of sibling differentiation.

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 a clear use context: 'Useful for understanding the current state of the semantic search system.' This implies when the tool is appropriate, but it offers no explicit guidance about when not to use it or which alternative sibling to prefer for narrower queries like version-only checks.

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