openEuler MCP Toolkit

by Logic-ze

Overview Schema Related Servers Score Discussions

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Server Quality Checklist

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Latest release: v0.1.0
Disambiguation4/5
Tools cover distinct areas like memory, filesystem, processes, and CPU scheduling, but some memory-related tools (get_memory_info, sample_memory_trend, get_process_memory) could be confused. Overall, each tool has a specific purpose with limited overlap.
Naming Consistency3/5
Names use mixed verb patterns (get_, monitor_, sample_, simulate_, analyze_) rather than a consistent verb_noun structure. While readable, the lack of pattern may cause hesitation in selecting the correct tool.
Tool Count5/5
With 12 tools, the count falls well within the ideal 3-15 range for a system toolkit. Each tool serves a clear function without unnecessary bloat or sparseness.
Completeness3/5
The toolkit covers memory, filesystem, process, and CPU scheduling domains, but lacks basic tools like listing all processes, CPU info, or network stats. Notable gaps exist for a comprehensive system toolkit.
Average 3.2/5 across 12 of 12 tools scored. Lowest: 2.4/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 1 commit in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It only states it simulates and reports metrics, but does not mention side effects, state changes, or that it is a pure simulation without persistent effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, concise but lacking detail. It is front-loaded with the primary action, but could include additional information in a second sentence.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description fails to explain input parameters (jobs array structure, algorithm options, time_slice). It is insufficient for an agent to use the tool correctly without inferring from the schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 33% (only algorithm described). The description adds no explanation for parameters like jobs or time_slice, failing to compensate for the low schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool simulates CPU scheduling and reports waiting, turnaround, and response metrics. It distinguishes from sibling tools like simulate_page_replacement by specifying the type of scheduling.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives (e.g., simulate_page_replacement). It lacks context about prerequisites or suitable scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 fails to mention whether the tool has side effects, requires permissions, alters system state, or what 'classify' entails. The description is too vague to ensure safe invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is concise and front-loaded with the primary action. However, it could be slightly more structured by separating the sampling and classification aspects. Still, it is appropriately sized for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Although an output schema exists (not shown), the description does not provide enough context for an agent to understand what the tool returns. With two parameters and zero schema coverage, the description should elaborate on sampling behavior and output format. It is incomplete for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning parameters are not documented in the schema. The description does not mention duration_seconds or interval_seconds, nor does it explain their purpose, defaults, or constraints. This is a critical gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: sampling system memory usage and classifying its short-term direction. This is a specific verb+resource combination that distinguishes it from siblings like get_memory_info (which likely returns current snapshot) and sample_cpu_time_ratios (CPU-focused).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. For example, it doesn't explain when to use sampling over get_memory_info, or how the classification differs from other monitoring tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must cover behavioral traits. It does not mention that the tool is read-only or its potential performance impact (e.g., scanning many files). The parameters max_depth and max_files imply safety limits, but the description does not explain these safeguards.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that front-loads the core purpose. However, it could be more structured by mentioning parameter defaults or usage hints, but there is no wasted text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While an output schema exists (mitigating need to explain return values), the description fails to elaborate on what 'largest paths' means or how file sizes are summarized. Given the tool's four parameters and potential complexity, the description is too brief.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 25%, and the tool description does not add any parameter details beyond the schema titles. Parameters like top_n and max_depth are not explained, and the description does not compensate for the low schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Summarize' and the resource 'file counts, sizes, extensions, and largest paths in a directory'. It distinguishes the tool from sibling tools which are all memory/process related, making its purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, nor any prerequisites or limitations. Sibling tools are dissimilar, so confusion is low, but explicit usage guidance is missing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present. The description does not disclose any behavioral traits such as side effects, output format, or performance implications. It merely repeats the algorithmic options.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one sentence, which is concise but lacks necessary details. It is front-loaded with the key action, but the brevity sacrifices completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of page replacement simulation, the description is too sparse. It does not hint at the output (e.g., page faults, hit ratio) or explain how parameters affect results. Even with an output schema present, the description should provide context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no meaning beyond the parameter schema. The algorithm list is already in the schema; frame_count and reference_string are not elaborated. With 67% schema coverage, the description fails to compensate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool simulates page replacement using FIFO, LRU, CLOCK, or optimal algorithms. It distinguishes from sibling tools like simulate_cpu_scheduling and simulate_disk_allocation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, or on selecting among the four algorithms. There is no mention of prerequisites or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so description carries full burden. It states a read-like operation (sampling) and normalization, but does not explain side effects, permissions, or what 'per-state ratios' means. Minimal behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with no wasted words. Efficient but could be slightly expanded without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Output schema exists but description does not explain return format or state meaning. No context on how sampling works or relationship to sibling tools. Incomplete for a tool with parameters and output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and description does not mention parameters 'duration_seconds' or 'interval_seconds'. No meaning added beyond schema defaults and ranges.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses specific verbs 'sample' and 'normalize' with clear resource 'CPU time deltas' and outcome 'per-state ratios'. It distinguishes from siblings like get_memory_info or simulate_cpu_scheduling by focusing on sampling and ratio normalization.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
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 alternatives like simulate_cpu_scheduling. The description implies it is for sampling CPU time ratios, but lacks context on conditions or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It notes 'Read' indicating read-only and 'bounded' suggesting limits, but does not disclose details like snapshot nature, potential recursion cost, or that parameters control bounds. The output schema helps but description remains thin.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence is concise but under-specified. Every word is functional, yet critical parameter info is missing. Could be more informative without sacrificing brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 3 parameters and no annotations, the description should detail parameter behavior. It only identifies root PID, ignoring depth and node limits. Despite an output schema, the missing parameter context leaves the tool incomplete for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% and description only mentions 'root PID' implicitly via 'selected root PID'. It fails to explain max_depth and max_nodes parameters, leaving their semantics entirely to the schema. The description adds negligible value beyond parameter names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it reads a bounded parent-child process tree from a selected root PID, using specific verb 'Read' and precise resource. No sibling tools overlap with process trees, so differentiation is inherent.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this vs alternatives. However, sibling tools are unrelated (memory, file, CPU), so confusion is minimal. Implied usage for reading process hierarchies, but lacks when-not or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only mentions 'when available' for inode counts. It does not disclose potential behavior like permissions required, system impact, or edge cases. Minimal transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, 12 words, front-loaded with the action verb. No unnecessary words or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With zero parameters and an output schema, the description is adequate but minimal. It does not elaborate on return values or typical use cases, which could be helpful given the sibling toolset.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist, so baseline is 4. The description adds no parameter information, but none is needed since schema is empty.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it reads mounted filesystems and provides space usage and inode counts. The verb 'Read' and resource 'mounted filesystems' are specific, and the data types are listed. It distinguishes from sibling tools like get_memory_info but does not explicitly differentiate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as get_memory_info or monitor_file_metadata. The description lacks context for appropriate usage scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description only states 'metadata polling' without disclosing read-only nature, side effects, authorization needs, or rate limits. Minimal behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no wasted words. The first sentence identifies the action and target, the second clarifies what the tool does not do. Efficient and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite an output schema existing, the description does not mention return values or behavior (e.g., polling starts immediately, returns array of snapshots). Lacks critical context for a polling tool with configurable parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Only the path parameter has a schema description (33% coverage). The tool description adds context that duration_seconds and interval_seconds control polling timing, but does not explain each parameter in detail.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool polls file size and timestamps, and explicitly distinguishes it from access tracing, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., get_filesystem_info or analyze_file_distribution). The negative hint about access tracing is present but insufficient for making informed tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. 'Simulate' implies no real-world changes, but it does not explicitly state the simulation is non-destructive or read-only. Adequate but 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, efficient sentence with no redundant words. However, it could be slightly more structured to improve readability without adding length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of the input schema (nested objects, multiple parameters) and the lack of annotations, the description is too minimal. It does not explain when to provide DiskScenario or the meaning of allocation strategies, leaving gaps for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 33% (only strategy parameter has a description). The tool description adds no additional meaning beyond the schema, leaving parameters like total_blocks and block_size_bytes unexplained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly specifies the verb 'simulate' and the resource 'disk block allocation' with three explicit strategies (contiguous, linked, indexed), distinguishing it from sibling tools like simulate_page_replacement.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., simulate_page_replacement) or any exclusions. The description lacks context for appropriate invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description only mentions sampling deltas but does not disclose behavioral traits like permissions, limitations, or whether it's poll-based.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with no fluff, front-loaded verb 'Sample', efficient for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Lacks completeness given 3 parameters and no annotations. Does not explain return values or how to interpret deltas, despite having an output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% yet the description adds meaning by linking 'pid' to per-process sampling and 'deltas' to output type. However, it does not explain other parameters or their interaction.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool samples context-switch deltas, either system-wide or per-process, distinguishing it from siblings like memory or CPU tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
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 alternatives. The purpose is implied but lacks context for decision-making.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description labels the tool as 'Read', indicating a non-destructive, read-only operation. However, with no annotations to provide safety guarantees, the description lacks further behavioral context (e.g., permissions required, impact on system, rate limits). It is adequate but not enriched beyond the basic read indication.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is front-loaded with the action ('Read') and immediately conveys the key resources. It contains no filler or redundant information, making it concise and effective for quick comprehension.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 parameters, output schema present), the description covers the essential functionality. The presence of an output schema reduces the need to explain return values. However, it lacks contextual completeness regarding prerequisites (e.g., process existence, permissions) or strictness of inputs (e.g., pid validity), leaving minor gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema coverage, the existing parameter descriptions are clear. The description adds value by mentioning 'largest memory mappings' which hints at the mapping_limit parameter's purpose, but it does not significantly augment what the schema already provides (e.g., mapping_limit's description already states 'sorted by RSS'). Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Read' and the specific resources: 'RSS, VMS, and the largest memory mappings for one process.' This distinguishes it from siblings like 'get_memory_info' (likely broader) and 'sample_memory_trend' (temporal focus), providing a specific and actionable purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or when-not-to-use guidance is provided. The description implies it is for reading detailed memory of a single process, but it does not compare with alternatives such as 'get_memory_info' or 'sample_memory_trend', leaving the agent to infer usage context without clear boundaries.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description correctly indicates a non-destructive read operation. It does not elaborate on permission needs or execution time, but the tool is simple enough that the description is sufficient for safe invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-formed sentence with no extraneous information. It is front-loaded with the action and resource.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters, has an output schema, and is a simple read operation, the description is largely complete. However, it could briefly mention that it provides a system-wide snapshot to differentiate from process-specific alternatives.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, so the description has no additional meaning to add beyond the input schema. Per the guidelines, parameter semantics score baselines at 4 for 0 parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool reads current system RAM, swap, and /proc/meminfo values. It uses a specific verb ('Read') and resource, and distinguishes itself from siblings like get_process_memory (process-level) and sample_memory_trend (time series).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide guidance on when to use this tool versus alternatives. It implicitly suggests it is for a one-shot system-wide memory snapshot, but no explicit when-to-use or when-not-to-use information is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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