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 exact command executed ('docker compose logs --tail=N --no-color SERVICE | grep PATTERN') and the behavior of returning only matches. It also clarifies accepted formats for since/until, adding useful context beyond basic purpose.

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 well-structured: it starts with the purpose, then gives the command, then provides a comparative benefit, and ends with a parameter note. Every sentence adds value with 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?

Given the tool has 8 parameters, no output schema, and no annotations, the description covers the essential aspects: purpose, command behavior, returned data (only matches), and time parameter formats. It could be more complete by specifying output format or prerequisites, but it is sufficient for an agent to select and 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?

Schema coverage is 100%, so baseline is 3. The description adds meaning by showing how parameters map to the shell command (e.g., tail=N, SERVICE, grep PATTERN) and reiterates the since/until format in a compact way. This is helpful but not extensive, meriting a 4.

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 clear purpose: 'Поиск по логам Docker-контейнеров на удалённом VPS' (search Docker container logs on remote VPS) and explicitly differentiates from the sibling docker_logs by noting it returns only matching lines and is more economical for targeted search. This makes the tool's function and distinction unambiguous.

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 provides a direct usage comparison: 'Экономичнее docker_logs для прицельного поиска — возвращает только строки с совпадением' (More economical than docker_logs for targeted search — returns only matching lines). This clearly indicates when to prefer this tool, though it does not explicitly state when not to use it or mention other 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?

With no annotations, the description carries full responsibility. It discloses the two major behavioral defaults (error-only filtering, 300-char truncation) and the accepted time formats for since/until. It does not explicitly state the operation is read-only, but 'shows logs' implies non-mutating behavior.

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 short sentences, each serving a distinct purpose: purpose, defaults/rationale, alternative tool, and time format guidance. No redundant text; information is 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?

The description covers the tool's purpose, defaults, alternatives, and time formats, which is sufficient given the 100% schema coverage. It lacks an output format example and failure-mode details (e.g., no logs found), but overall provides a solid mental model for a read-only log 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%, and the description only reiterates what the schema already states about since/until formats and defaults. It adds no new parameter semantics beyond the structured definitions, so the baseline 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 a specific action (show last lines of logs) on a specific resource (Docker service on a remote VPS), and clearly distinguishes from docker_grep by noting pattern search is handled there. It also describes key defaults (errors only, truncation) that scope the tool's behavior.

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 directs users to docker_grep for targeted pattern searches, offering a clear alternative. The description implies this tool is for general log viewing with error hints, but does not explicitly list when-not-to-use cases or prerequisites beyond that.

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 behavioral disclosure burden. It explicitly states the command executed and that it runs on a remote VPS, implying a read-only status check. While it does not detail error handling or output structure, 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?

The description is two sentences, front-loaded with the main purpose and including the exact command and usage intent. Every sentence earns its place with no waste.

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 status-checking tool with a single well-documented parameter, the description covers purpose, command, and usage. The mention of JSON output compensates for the lack of an output schema, making the tool fully understandable in context.

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 already documents the single 'project' parameter with a description of what it is (local path to project folder). With 100% schema description coverage, the description adds no additional parameter semantics, so baseline 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 purpose: showing the status of all Docker containers for the project on the remote VPS. It names the exact command executed ('docker compose ps --format json') and explicitly says it is used to check which containers are running, distinguishing it from sibling tools like docker_logs or docker_stats.

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 a clear usage context: 'Use to check which containers are running.' It does not explicitly mention when not to use it or name alternatives, but the context is specific enough for an agent to select it appropriately when checking container status.

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 exact command ('docker stats --no-stream --no-trunc --format json'), making the behavior fully transparent. It doesn't discuss permissions or side effects, but the operation is inherently read-only and the command itself implies a non-streaming snapshot.

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, well-structured sentences: first states the purpose, second gives the command and usage. Every sentence 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 low-complexity tool with one parameter and no output schema, the description adequately covers what it does, how it does it, and when to use it. It doesn't describe the return format in prose, but the command includes '--format json', which implies the output structure.

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 already covers the single parameter with a clear description (local path to project folder), so the description adds no additional parameter-level information. The baseline of 3 applies due to 100% 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 explicitly states the tool reports CPU and RAM consumption for project containers, which is a specific and distinct function from sibling tools like docker_logs or docker_ps. It even names the exact command executed, reinforcing the purpose.

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 includes a direct usage instruction: 'Use to check server load,' giving clear context for when the tool is appropriate. However, it does not mention when not to use it or compare with alternative tools, so it falls short of explicit exclusion 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?

No annotations are provided, so the description carries the burden. It discloses that it executes multiple commands and gathers results, implying a read-only health check. However, it doesn't explicitly state permissions or whether it modifies anything, leaving some ambiguity for a tool with no annotation safety hints.

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, front-loaded with the key information. Every word earns its place, and it avoids redundancy with the schema.

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-parameter tool with no output schema, the description adequately covers what it does, when to use it, and how it works (multiple commands). It lacks explicit mention of return format, but that is not critical given the context and sibling tool set.

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% with a clear description for the only parameter (project path). The tool description adds no extra meaning beyond the schema, so baseline 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 clearly states the tool gathers general VPS information (uptime, disk, memory, container status) and collects results from multiple commands. It distinguishes itself from Docker-specific sibling tools like docker_ps and docker_stats, making its scope 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?

Explicitly says 'Use to quickly assess server health', which gives clear context for when to use. It does not explicitly exclude alternatives like docker_stats for container-level details, but the server-wide scope is implied enough for a distinct use case.

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