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

No annotations are provided, so the description carries the behavioral burden. It does disclose the output shape ('normalized scores, system breakdowns, and interpretation'), which is useful, but it does not mention failure modes, required parameter count, or edge cases. For a pure calculation tool, this is acceptable but not rich.

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 action and object come first, and the return summary is contained in a single clause. Every word contributes to understanding.

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 compute-only tool, the description covers both the operation and the return payload, and the schema fully covers inputs. There is no output schema, so the description appropriately explains return values. It could be more complete with usage guidance and edge-case behavior, but nothing essential is missing for invoking the tool successfully.

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%, with all four parameters documented in the input schema. The description adds only a high-level 'patient parameters' framing and the 8-system framework, so it does not materially improve on the schema's parameter documentation.

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 ('Calculate') and resource ('health scores'), and adds the 8-system framework and return type. It is clearly distinct from siblings like recommend_smart_cards and generate_care_plan, though it does not explicitly name or contrast them.

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 alternatives such as generate_care_plan or recommend_smart_cards. The context is only implied by 'based on patient parameters'; there are no explicit prerequisites, exclusions, or alternative routing.

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 full burden. It discloses the informational outputs but does not explicitly state that the tool is non-destructive, whether it performs network fetches to detect 'available updates', or any side effects. 'Check' implies read-only but leaves key behavioral aspects unstated.

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 zero fluff. The action and target resource are front-loaded, followed by the concrete outputs. Every sentence earns its place without 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?

For a simple tool with one optional parameter and no output schema, the description is largely complete: it names the outputs (branch, uncommitted changes, available updates) that an agent would need. The absence of explicit statements about network usage or non-mutating behavior leaves a small gap, but overall it is sufficient for correct invocation.

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 single 'repo' parameter is fully documented in the schema with an enum (knowledge-base, mcp-server, both) and a clear description including the default. Since schema coverage is 100%, the description need not add more; the tool description's mention of the two repositories aligns with the enum values.

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: 'Check Git status of repositories (knowledge base and/or MCP server)'. It enumerates the exact outputs shown (current branch, uncommitted changes, available updates), making it clearly distinct from sibling tools like pull_git_updates or sync_repositories, which imply mutating operations.

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 read-only inspection use case is implied through 'Check' and 'Shows', and the tool's outputs suggest checking before updating. However, it never explicitly states when to prefer this over siblings like pull_git_updates or sync_repositories, nor does it provide exclusions or prerequisites.

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 full behavioral burden. It only states that a care plan is generated and references a framework; it does not disclose whether the plan is returned as data, persisted, or accompanied by any side effects, authorization requirements, or rate limits. This is minimal beyond what the name already implies.

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?

A single, front-loaded sentence that wastes no words. It states the action, the object, the key inputs, and the framework, with every phrase contributing to tool identification.

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 schema fully documents all parameters, making the invocation path reasonably clear. However, with no annotations and no output schema, the description fails to explain the result format or behavioral outcomes, leaving a noticeable gap for a healthcare-related generation 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 description coverage is 100%, so the baseline is 3; the description merely echoes the parameter names (age, conditions, goals) without adding constraints, formats, or relationship details. The schema itself already provides meaning, examples, and optional lifeStage auto-determination.

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 ('Generate') with a concrete resource ('personalized care plan') and names the key inputs ('patient age, conditions, and goals') plus the guiding framework ('Performance Medicine framework'). This clearly distinguishes it from sibling tools like calculate_health_score and recommend_smart_cards, which operate on different outputs.

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 intended use is implied: an agent should call this tool when it needs to generate a personalized care plan. However, there are no explicit alternatives, exclusions, or conditions for when to prefer this over sibling tools such as calculate_health_score or recommend_smart_cards.

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 present, so the description carries the full burden. It transparently indicates a read-only operation ('Get') and the result is 'complete content'. However, it does not disclose behavior for missing files, folder search semantics, or partial-name matching that the schema hints at.

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 just two sentences: the first gives the core action, the second provides a practical use case. Every sentence earns its place, with no redundant or fluf 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 simple two-parameter tool with a complete schema, the description adequately covers the core purpose and use case. 'Complete content' also communicates the return value, compensating for the lack of an output schema. It misses an explicit pointer to search_files for discovering files, but that is more of a usage guideline gap.

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 input schema already documents both parameters. The description adds no extra parameter semantics beyond emphasizing retrieval 'by name', which matches the filename property, so the baseline score of 3 applies.

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 the specific verb 'Get' with a clear resource ('complete content of a specific file by name') and identifies the use case ('read full documentation'). It is easily distinguishable from sibling search_files because it is about content retrieval of a specific file, though it does not explicitly name the alternative.

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?

'Useful when you need to read full documentation' provides clear context for when to choose this tool. However, it does not explicitly state when not to use it or compare it with sibling tools like search_files, so it stops 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 present, the description carries the full behavioral disclosure burden. It does disclose one important side effect: pulling the knowledge-base repo automatically refreshes the knowledge map. However, it does not mention other behavior an agent should know, such as whether local changes may be overwritten, how merge conflicts are handled, or whether network or authentication failures are possible.

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 concise sentences with no filler. It front-loads the main action and resource, then adds the most important behavioral nuance in the second sentence. Every word contributes.

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 tool with two optional parameters and no output schema, the description covers the core action and the auto-refresh side effect. However, it omits any mention of return/result format and gives no guidance for choosing among the closely related sibling tools, leaving some ambiguity for an agent.

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 both parameters fully: repo has an enum with defaults, and autoRefresh has a default and description. Schema description coverage is 100%, so the description does not need to add much. The tool description only restates the autoRefresh concept ('Automatically refreshes knowledge map') without adding any new parameter-level meaning.

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 names a specific verb and resource: 'Pull latest changes from Git remote for knowledge base and/or MCP server.' It also includes the notable side effect of refreshing the knowledge map, which adds specificity. It does not explicitly distinguish itself from the sibling sync_repositories, but the 'pull' framing and repo scoping make the purpose reasonably clear.

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 about when to use this tool versus alternatives such as sync_repositories, check_git_status, or refresh_knowledge_base. The phrase 'Pull latest changes' implies a use case, but the description never states when-not-to-use this tool or which sibling would be better for status checks or standalone refreshes.

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 full burden of disclosing behavior and side effects. It only says 'Find relevant,' which implies a read-only retrieval and relevance ranking, but it does not state whether anything is modified, what a SMART card contains, or what happens when no matches are found.

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 with no filler or redundant clauses. It clearly conveys the tool's purpose and is easy for an agent to parse quickly.

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 three-parameter retrieval tool with a fully documented schema and no nested objects, the description is sufficient for an agent to select and invoke it correctly. It falls short of 5 because the return value is described only as 'cards' and no behavioral caveats or edge cases are mentioned.

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%, and the schema already documents condition, maxCards, and cardTypes with examples. The description repeats the 'condition or health goal' idea without adding meaningful parameter-level detail 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 states a specific action ('Find') and resource ('SMART cards'), and clarifies that these are medical and behavioral interventions. It is clear, but it does not explicitly contrast with sibling tools such as generate_care_plan or calculate_health_score, so it stops short of a 5.

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 'for a specific condition or health goal' implies when the tool should be used. However, there is no explicit when-not-to-use guidance or mention of alternative tools, so usage guidance is largely 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.

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

No annotations are provided, so the description carries the full burden of explaining behavior. It discloses that this is a manual trigger and that automatic watching is the normal path, but it does not describe side effects, duration, idempotency, or what the return value looks like. Some behavior is conveyed, but not fully.

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 short sentences with no wasted words. The core action is front-loaded, and the usage caveat is stated immediately in a compact follow-up sentence.

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 a zero-parameter trigger, the description covers the essential purpose and the main usage caution. It could mention what happens after the refresh or any output it returns, but for invoking the tool correctly the current description is largely sufficient.

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, so the schema already fully defines the invocation surface. The description adds no parameter-level detail, but none is needed; baseline 4 is appropriate for a no-parameter tool.

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 action ('refresh the knowledge base') and the intended outcome ('detect newly added files'). It is clear enough to distinguish from the listed sibling tools, though it does not explicitly name a sibling to differentiate from.

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 context for when the tool is not needed ('Usually not needed as file watching is automatic'), effectively telling the agent to avoid redundant calls. It doesn't spell out explicit conditions for use, but the implication that manual refresh is only for exceptional cases is clear.

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 burden of explaining behavior. It explicitly says the tool searches across all knowledge base files and returns excerpts with context, giving a clear read-oriented behavior. It does not mention details like case sensitivity, result ordering, or failure behavior, but the core behavior is transparent.

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 tightly written sentences, front-loaded with the primary action and scope. Every word adds value, and there is 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?

The description is adequate for calling the tool but leaves gaps because there is no output schema. 'Returns relevant excerpts with context' is vague about what fields are included (e.g., file name, match location), and the description does not mention behavior like maxResults implications or no-match outcomes.

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%, with each parameter having a meaningful description. The tool description adds little beyond the schema, only reinforcing that search is across all files. Per the calibration baseline, this is adequate but not exceptional.

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 ('Search'), the resource ('all knowledge base files'), and the output ('relevant excerpts with context'). It distinguishes itself from siblings like get_file_content by focusing on cross-file keyword search rather than retrieving a specific file's content.

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 searching across knowledge base files—but it does not explicitly state when not to use it or name alternatives. The contrast with get_file_content is left implicit rather than stated.

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 the core behavior: checking status and pulling updates, and reveals the check-only mode. It does not mention potential side effects like overwriting local changes or merge conflicts, but 'pull updates' reasonably signals a mutating operation.

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 short sentences with no wasted words. The main action is front-loaded ('One-click sync: Check status and pull updates'), and the check-only option is added as a separate clarifying sentence.

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 optional, well-documented parameter and no output schema, the description covers the essential invocation details: what it does, the scope (all repositories), and the available mode. It is slightly lacking in return-value or error-case expectations, but overall adequate for its low complexity.

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 adds a small amount of context by explaining check-only mode is 'to see what updates are available,' which maps to the checkOnly parameter, but it does not add meaning beyond what the schema already conveys.

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 action ('Check status and pull updates') on a clear resource ('all repositories'), and mentions 'check-only mode', which adds nuance. It does not explicitly contrast with the sibling tools check_git_status and pull_git_updates, but the combined 'one-click sync' behavior is clear enough to understand its scope.

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: it is a combined status-check and pull operation, and check-only mode is suggested 'to see what updates are available.' However, it does not explicitly say when to use this tool versus the sibling tools check_git_status or pull_git_updates, leaving the choice somewhat to inference.

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