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 behavioral disclosure. It indicates the tool returns 'every architecture and repository memory,' implying a potentially large and unfiltered result, but it does not warn about response size, formatting, read-only nature, or whether the data is a snapshot or live. For an unannotated tool, more behavioral context would be valuable.

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 short sentences, both earning their place: the first states the trigger condition, the second states the return value. No filler or repetition. Information is front-loaded with the call condition before the output description.

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 tool with no output schema, the description provides a basic sense of what will be returned ('every architecture and repository memory') and when to use it. However, it does not describe the structure or format of the returned data, nor clarify what 'architecture' and 'repository memory' exactly contain. Given the absence of an output schema, the description 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 tool has zero parameters, so there are no parameters to document. The baseline of 4 applies because the description does not need to clarify parameter meaning, and it correctly mentions the 'broad structural overview' scope, which is the only relevant input 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?

Description states a clear verb and resource: 'get' a 'broad structural overview of the repository' and returns 'every architecture and repository memory.' This distinguishes it from siblings like search_memory and get_timeline because it emphasizes completeness ('every') rather than targeted lookup or filtering. Some ambiguity remains about what 'architecture' and 'repository memory' concretely mean, but the core purpose is understandable.

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?

Provides an explicit invocation condition: 'Call when you need a broad structural overview of the repository.' This is clear context for when the tool should be selected. It does not explicitly name alternatives or state when not to use it, so it falls short of a 5, but the guidance is effective for a zero-parameter tool.

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 behavioral disclosure burden. It discloses that the result includes the gap and every explicitly referenced memory, revealing the tool's fetching scope. It does not mention error cases or direct-vs-recursive reference handling, so it is not exhaustive.

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 short sentences: the first tells when to call, the second tells return behavior. Every word earns its place with no 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 one-parameter read tool with full schema coverage, the description tells the agent when to call and what to expect back. It could be richer about how referenced memories are returned, but the low complexity means nothing essential 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?

Schema description coverage is 100%, and the only parameter 'id' is already described as 'Gap memory ID.' The description adds context about the gap but no additional parameter-level detail, matching the baseline for 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 states the tool returns a single known gap plus every memory it explicitly references, clearly identifying the object and scope. The phrase 'one known gap' distinguishes it from siblings like list_gaps and search_memory without requiring schema inspection.

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?

It opens with an explicit trigger condition: 'Call when you need the full context for one known gap.' It does not name alternatives or list exclusion cases, so it stops short of full routing guidance.

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 correctly communicates that this is a read-like retrieval operation returning two relationship directions. However, it does not disclose potential limits, ordering, pagination, or error behavior, which would be useful given the absence of annotations and 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?

The description is two short sentences with no redundant phrasing. The when-to-use trigger is front-loaded, and the return semantics are stated directly afterward.

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 single-parameter retrieval tool, the description explains when to call it and what the result contains. It still leaves some details about result format and relationship depth to inference, but it is adequate for the tool's simplicity.

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 only parameter, memory_id, is already documented as 'Memory ID.' The description adds no new meaning to the parameter beyond identifying it as the anchor memory, so the baseline score 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 names a specific operation and resource: retrieve context connected to a particular memory. It also specifies the exact output shape (referenced and referencing memories), which makes it easy to distinguish from sibling tools like search_memory or list_gaps.

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?

It gives a clear invocation condition ('Call when you need context connected to a particular memory'). It does not explicitly say when not to use it or name sibling alternatives, but the condition is specific enough for an agent to select it.

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 behavioral burden. It discloses that results are ordered newest first and that the output consists of commit, release, and timeline memories. It doesn't cover pagination or format, but for a read-only no-param tool 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 compact sentences lead with the trigger condition and then state the return behavior. Every clause is informative and there is no 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 parameterless tool with no output schema, the description gives the key decision context and summarizes the returned data. It could add detail on what 'timeline memories' means, but the core information needed to call and interpret the result is present.

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?

There are zero parameters, so the schema already covers everything. Baseline 4 applies; the description doesn't need to explain parameter 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?

Description states a clear purpose: retrieving repository history, releases, and recent change context, and specifies the returned content (commit, release, timeline memories). It doesn't explicitly differentiate from sibling tools like search_memory, but the 'repository history' framing makes the focus reasonably distinct.

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?

'Call when you need repository history, releases, or recent change context' gives explicit triggering conditions. It does not name alternatives or exclusion cases, but the condition is specific enough to guide selection among the listed siblings.

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 usefully states that the tool returns all gap memories, orders them by severity, and includes their location. This conveys the output behavior well for a zero-parameter read operation, though it does not explicitly state that it has no side effects.

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. The invocation condition is front-loaded, and the return details are stated efficiently. Every sentence adds distinct value.

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 parameterless list tool with no output schema and no annotations, the description provides enough context: what the tool finds, what it returns, and how results are ordered. Nothing essential for calling it correctly 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, so there are no parameter semantics to clarify. The baseline for a parameterless tool is 4, and the description does not introduce confusion by referencing nonexistent arguments.

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 verb and resource: 'find known missing, risky, or incomplete parts of the repository' and 'returns all gap memories.' The description clearly distinguishes this from siblings like get_gap (single item) and search_memory (general search) by framing it as a comprehensive listing operation.

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?

Provides a clear trigger condition: 'Call when you want to find known missing, risky, or incomplete parts of the repository.' However, it does not explicitly mention when not to use it or name alternatives such as get_gap for retrieving a single gap memory, so it stops short of full routing guidance.

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 does disclose the output shape by listing the grouping categories, which is useful. However, it does not mention matching semantics, result limits, ordering, or what happens when no memories match.

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. The trigger condition is front-loaded and the output grouping is stated efficiently.

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 single-parameter search tool with no nested objects or output schema, the description covers the main invocation context and what kind of results to expect. It could mention result-level details or explicitly route to siblings for specific slices, but it is sufficient for basic correct 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 100% and the single query parameter is already described as 'The repository question or search terms.' The description adds the notion of relevance to a task/question, but it does not substantially expand on the schema-provided parameter 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 states a specific action: searching repository context relevant to a question or task, and describes the returned result as matching memories grouped by architecture, files, dependencies, packages, repository, commits, and gaps. This makes the purpose clear, though it does not explicitly differentiate itself from the get_* and list_* siblings beyond implying a broader search.

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?

It explicitly says 'Call when you need repository context relevant to a question or task,' giving a clear trigger for use. It does not state when not to use it or name alternatives, but the context is strong enough for an agent to choose it over more targeted gap/architecture tools.

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