此仓库包含一个小型 MCP 服务器，用于查询来自 tools/health/reports 的 Apache Incubator 健康报告。
它解析 Apache 健康工具所使用的 Markdown 报告格式，并提供以下 MCP 工具：
列出可用的孵化项目报告
搜索孵化项目名称
获取单个孵化项目的解析摘要
返回原始 Markdown 报告
返回特定时间窗口的指标
比较单个孵化项目在两个或三个窗口下的数据
列出支持的指标和窗口
按窗口（如 3m、6m 或 12m）内的指标对孵化项目进行排名
将服务器指向包含 Markdown 文件的本地目录，例如：
reports/
Amoro.md
Iggy.md
...该解析器是围绕当前的 Apache 报告结构设计的，特别是 ## Window Details 部分。
Related MCP server: IPMC MCP
python3 -m venv .venv
source .venv/bin/activate
python3 -m pip install .对于本地开发：
make install-devhealth-mcp --reports-dir /path/to/incubator/tools/health/reports该服务器使用 stdio，因此旨在由 MCP 客户端启动。
对于未先安装的本地开发，您仍然可以直接启动 stdio 服务器：
python3 server.py该软件包还保留了 apache-health-mcp 作为向后兼容的命令别名。
编辑 ~/Library/Application Support/Claude/claude_desktop_config.json 并添加：
{
"mcpServers": {
"apache-health": {
"command": "health-mcp",
"args": [
"--reports-dir",
"/path/to/incubator/tools/health/reports"
]
}
}
}然后重启 Claude Desktop。如果您安装在不在 PATH 中的虚拟环境中，请使用该环境 health-mcp 命令的绝对路径。
health_overview
返回报告目录、报告数量、孵化项目列表以及最新生成日期。
list_podlings
返回报告目录中可用的孵化项目名称。
search_podlings
通过不区分大小写的子字符串搜索孵化项目名称，并可选择结果限制。
get_report_summary
返回单个孵化项目的解析窗口指标。
get_report_markdown
返回单个孵化项目报告的原始 Markdown。
get_window_metrics
返回单个孵化项目和一个窗口（如 3m、6m、12m 或 to-date）的指标，包括 trends 下的标准化趋势词，如 up（上升）、down（下降）和 flat（平稳）。
compare_windows
返回单个孵化项目在两个或三个窗口下的并排指标，包括每个窗口 trends 下的标准化趋势词。
query_metric_rankings
按解析后的指标（如 commits、prs_merged、dev_messages、bus50 或 median_merge_days）对孵化项目进行排名。
list_metrics
返回支持的指标名称和可查询的可用窗口。
这些示例展示了用户可以向连接到此服务器的 MCP 客户端提出的问题类型。
“此检出中有哪些 Apache Incubator 健康报告可用？”
“我们有多少份孵化项目健康报告，它们是什么时候生成的？”
“哪些孵化项目有我可以查询的健康报告？”
“我可以询问哪些健康指标和报告窗口？”
“向我展示 Amoro 的健康摘要。”
“最新的健康报告对 Iggy 有什么评价？”
“查找名称中包含 'stream' 的孵化项目并总结最佳匹配项。”
“对于这个孵化项目，显示最近 3 个月的健康指标。”
“向我展示 Amoro 的原始 Markdown 报告，以便我可以检查来源。”
“比较 Amoro 的 3 个月、6 个月和 12 个月活动情况。”
“Iggy 的开发活动是在改善还是在放缓？”
“比较该孵化项目最近的邮件列表活动与长期趋势。”
“该孵化项目的 PR 合并活动在 3 个月和 12 个月窗口之间是否有变化？”
“该孵化项目的关键人员因素（bus factor）在报告窗口中是变好了还是变差了？”
“过去 3 个月内开发列表消息最多的孵化项目是哪些？”
“向我展示过去 3 个月内没有提交记录的孵化项目。”
“哪些孵化项目的 PR 合并中位数时间最长？”
“按 6 个月窗口内的合并 PR 数量对孵化项目进行排名。”
“查找最近报告窗口中审阅者多样性较低的孵化项目。”
“根据最近的活动，给我一份可能需要导师关注的孵化项目简短列表。”
“哪些孵化项目在提交、PR 和开发列表消息方面看起来很安静？”
“查找近期活动较少的孵化项目，并将它们与 12 个月的趋势进行比较。”
“我应该手动审查哪些孵化项目的关键人员因素或审阅者多样性问题？”
常见任务可通过 make 完成：
make format
make lint
make typecheck
make test
make coverage
make check此服务器查询的是已生成的报告文件。它不会运行 Apache 的上游收集脚本。
此处的工作区不包含本地 reports/ 目录，因此服务器被构建为接受 Apache 报告目录的任何本地克隆或复制的快照。
Compare one podling across two or three windows.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It mentions 'compare' but doesn't specify whether this is a read-only analysis, if it requires specific permissions, what the output format is, or any rate limits. For a tool with zero annotation coverage, this is a significant gap in transparency about how the tool behaves operationally.
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, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized for a tool with no parameters and is front-loaded with the core action. Every part of the sentence contributes to understanding the tool's function.
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 no annotations, no output schema, and 0 parameters, the description is incomplete for effective use. It doesn't explain what 'compare' entails (e.g., metrics compared, output format), behavioral traits, or usage context relative to siblings. For a comparison tool in a metric-focused server, more detail is needed to guide the agent adequately.
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 has 0 parameters with 100% coverage, meaning no parameters are documented in the schema. The description doesn't add parameter details, but since there are no parameters, this is acceptable. The baseline for 0 parameters is 4, as the description doesn't need to compensate for missing param info.
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 action ('compare') and target resource ('one podling across two or three windows'), which is clear but somewhat vague. It doesn't specify what aspects are compared or how the comparison is performed. However, it distinguishes from siblings like 'list_podlings' or 'get_window_metrics' by focusing on comparison rather than listing or retrieving metrics.
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 on when to use this tool versus alternatives is provided. The description implies usage for comparing podlings across windows, but doesn't mention prerequisites, when-not-to-use scenarios, or how it differs from siblings like 'query_metric_rankings' or 'search_podlings' that might involve podling analysis. This leaves the agent without clear contextual boundaries.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Return the raw markdown for one podling report.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool returns raw markdown but doesn't explain how the report is selected, if authentication is needed, potential errors, or response format details. This leaves significant gaps for a tool that likely involves data retrieval.
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, efficient sentence that directly states the tool's function without any wasted words. It's front-loaded with the core action and resource, making it easy 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?
Given the complexity of retrieving a specific report (implied by 'one podling report'), no annotations, and no output schema, the description is incomplete. It doesn't explain how to specify which report, what the markdown contains, or error handling, leaving the agent with insufficient context for reliable 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?
The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add param info, but that's acceptable here. A baseline of 4 is appropriate since the schema fully handles the lack of parameters without requiring compensation from the description.
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 action ('Return') and resource ('raw markdown for one podling report'), making the tool's purpose understandable. However, it doesn't differentiate from sibling tools like 'get_report_summary' or explain what distinguishes 'raw markdown' from other report formats, preventing a perfect score.
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 no guidance on when to use this tool versus alternatives like 'get_report_summary' or 'search_podlings'. It lacks context about prerequisites, such as how to identify the specific podling report, or any exclusions, leaving usage unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get parsed metrics for one podling report.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but offers minimal behavioral insight. It implies a read operation ('Get') but doesn't disclose authentication needs, rate limits, error conditions, or what 'parsed metrics' entails (format, structure, or completeness). For a tool with zero annotation coverage, this leaves significant gaps in understanding its 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?
The description is a single, efficient sentence with zero waste. It's front-loaded with the core action and resource, making it immediately understandable without unnecessary elaboration.
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 no annotations, no output schema, and a tool that presumably returns parsed metrics, the description is incomplete. It doesn't explain what 'parsed metrics' includes, how the podling report is identified, or the return format. For a tool in a metric-heavy context with multiple siblings, more detail is needed to guide effective 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?
The tool has 0 parameters with 100% schema description coverage, so the schema fully documents the lack of inputs. The description adds value by specifying the resource ('one podling report'), implying it operates on a single, implicitly identified report. This contextual meaning goes beyond the empty schema, justifying a score above baseline.
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 verb ('Get') and resource ('parsed metrics for one podling report'), making the purpose understandable. It distinguishes from siblings like 'get_report_markdown' (which likely returns raw markdown) by specifying 'parsed metrics', but doesn't explicitly differentiate from 'get_window_metrics' or other metric-related tools.
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 no guidance on when to use this tool versus alternatives like 'get_report_markdown', 'get_window_metrics', or 'list_metrics'. It doesn't mention prerequisites, context for 'podling report', or when this tool is preferred over other metric-retrieval options.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Return metrics for a single podling/window combination.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden but only states what the tool returns without behavioral details. It doesn't disclose whether this is a read-only operation, potential errors, rate limits, or authentication needs, leaving significant gaps for a tool that likely queries metrics.
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, efficient sentence that directly states the tool's purpose with no wasted words. It is appropriately sized and front-loaded, making it easy to understand 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?
Given the tool has 0 parameters and no output schema, the description is minimally adequate but lacks completeness. It doesn't explain what metrics are returned, their format, or error handling, which are important for a metrics query tool with no structured output documentation.
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 has 0 parameters with 100% coverage, so no parameter documentation is needed. The description adds value by specifying that metrics are for a 'single podling/window combination', which clarifies the scope beyond what the empty schema provides, justifying a score above the baseline.
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 verb 'Return' and the resource 'metrics for a single podling/window combination', making the purpose specific and understandable. It doesn't explicitly distinguish from siblings like 'list_metrics' or 'query_metric_rankings', but the focus on a single combination provides some implicit differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description implies it's for a specific podling/window pair, but it doesn't mention prerequisites, when not to use it, or refer to sibling tools like 'list_metrics' for broader queries.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Return a high-level summary of the available Apache health reports.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool returns a summary but doesn't specify format, data freshness, rate limits, or authentication needs. This leaves critical operational details unclear for a tool that likely involves data retrieval.
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, efficient sentence that directly states the tool's function without unnecessary words. It's front-loaded with the core action and resource, making it easy 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?
Given the tool has 0 parameters and no output schema, the description adequately covers the basic purpose. However, for a health reporting tool in a server with multiple related siblings, it lacks context on output format or how it complements other tools, leaving gaps in overall understanding.
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 has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, focusing on the tool's purpose instead, which aligns well with the schema's simplicity.
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 verb ('Return') and resource ('high-level summary of available Apache health reports'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_report_summary' or 'get_report_markdown', which might offer similar functionality.
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 no guidance on when to use this tool versus alternatives like 'get_report_summary' or 'list_metrics'. It lacks context about scenarios where a high-level overview is preferred over detailed reports, leaving the agent without usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Return the supported metrics and windows for querying.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
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 states the tool returns data but doesn't disclose behavioral traits like whether it's a read-only operation, if it requires authentication, rate limits, or what the return format looks like (e.g., list, object). This leaves significant gaps for an agent to understand how to handle the tool.
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, efficient sentence that directly states the tool's purpose without any unnecessary words. It's front-loaded and wastes no space, making it 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?
Given the tool has no parameters and no output schema, the description is minimally adequate but lacks depth. It doesn't explain the return values (e.g., structure of metrics/windows) or any behavioral context, which could be important for querying tools. However, the simplicity of the tool (0 params) means the description isn't severely lacking.
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 has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter details, which is appropriate here, and it implies the tool takes no inputs, aligning with the schema. A baseline of 4 is given since no parameters exist and the schema fully covers them.
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 action ('Return') and the target ('supported metrics and windows for querying'), making the purpose understandable. However, it doesn't explicitly differentiate this tool from its siblings like 'get_window_metrics' or 'query_metric_rankings', which appear related to metrics/windows, so it doesn't reach the highest score.
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 no guidance on when to use this tool versus alternatives. With siblings such as 'get_window_metrics' and 'query_metric_rankings' that might overlap in functionality, there's no indication of context, prerequisites, or exclusions for using 'list_metrics'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List podlings that have a parsed markdown report.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
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 mentions the filter condition ('have a parsed markdown report') but doesn't disclose behavioral traits such as pagination, rate limits, permissions needed, or what happens if no podlings meet the criteria. For a tool with zero annotation coverage, this leaves significant gaps in understanding its 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 a single, efficient sentence that directly states the tool's purpose without any redundant information. It is appropriately sized and front-loaded, making it easy to understand at a glance.
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 0 parameters, no annotations, and no output schema, the description is minimal but adequate for a simple listing tool. It specifies a filter condition, which adds some context, but lacks details on behavior, output format, or integration with siblings, leaving room for improvement in completeness.
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 has 0 parameters with 100% coverage, so no parameter documentation is needed. The description adds value by specifying the filter condition ('have a parsed markdown report'), which provides context beyond the schema, though it doesn't detail how this filtering is applied internally.
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 action ('List') and resource ('podlings'), specifying that they must 'have a parsed markdown report'. This distinguishes it from generic listing tools by adding a filter condition, though it doesn't explicitly differentiate from sibling tools like 'search_podlings'.
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 provided on when to use this tool versus alternatives like 'search_podlings' or other siblings. The description implies usage for podlings with parsed markdown reports but doesn't specify exclusions, prerequisites, or comparative contexts with other tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Rank podlings by one parsed metric for a specific window.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
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 states the tool performs ranking, which implies a read-only operation, but doesn't disclose behavioral traits like whether it requires authentication, has rate limits, returns paginated results, or what the output format looks like. This is inadequate for a tool with zero annotation coverage.
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, efficient sentence that front-loads the core purpose ('Rank podlings') and adds necessary qualifiers ('by one parsed metric for a specific window') without any wasted words. It's appropriately sized for the tool's complexity.
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 no annotations, no output schema, and 0 parameters, the description is incomplete. It lacks details on behavioral aspects like authentication needs, rate limits, or output format, and doesn't clarify how it differs from siblings. For a ranking tool with no structured data, this leaves significant gaps for an AI 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 has 0 parameters with 100% coverage, so no parameter documentation is needed. The description adds context by specifying 'by one parsed metric for a specific window', which implies inputs might be inferred from context or defaults, but since there are no parameters, a baseline of 4 is appropriate as it doesn't need to compensate for gaps.
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 'Rank podlings by one parsed metric for a specific window', which provides a clear verb ('Rank'), resource ('podlings'), and scope ('by one parsed metric for a specific window'). However, it doesn't explicitly differentiate from siblings like 'get_window_metrics' or 'list_podlings', leaving ambiguity about when to use this versus those alternatives.
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 provided on when to use this tool versus alternatives. The description mentions ranking by a metric for a window, but it doesn't specify prerequisites, exclusions, or compare it to siblings such as 'get_window_metrics' or 'list_podlings', leaving the agent to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search podling names by case-insensitive substring.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the search is 'case-insensitive', which is useful, but fails to describe other critical behaviors like response format, error handling, or performance characteristics. This leaves significant gaps for a tool with zero annotation coverage.
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, efficient sentence that directly states the tool's function without any redundant or unnecessary information. It is front-loaded and appropriately sized for its purpose, earning a perfect score for conciseness.
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's simplicity (0 parameters, no output schema, no annotations), the description is adequate but incomplete. It covers the basic search action but lacks details on output format or behavioral context, making it minimally viable but with clear gaps in completeness.
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 has 0 parameters with 100% coverage, so no parameter documentation is needed. The description adds value by specifying the search mechanism ('case-insensitive substring'), which is not captured in the schema, justifying a score above the baseline of 3 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 clearly states the action ('Search') and resource ('podling names') with a specific constraint ('by case-insensitive substring'), making the purpose evident. However, it does not explicitly differentiate from sibling tools like 'list_podlings', which could serve a similar listing function, preventing a perfect score.
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 no guidance on when to use this tool versus alternatives, such as 'list_podlings' for unfiltered listing or other search-related tools. It lacks context on prerequisites, exclusions, or typical use cases, offering minimal usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v0.1.0compare_windowsget_report_markdownget_report_summaryget_window_metricshealth_overviewlist_metricslist_podlingsquery_metric_rankingssearch_podlingsScored across 9 tools
Each tool has a clearly distinct purpose with no overlap: compare_windows compares podlings across windows, get_report_markdown retrieves raw markdown, get_report_summary provides parsed metrics, get_window_metrics gives metrics for a single podling/window, health_overview offers a high-level summary, list_metrics enumerates supported metrics/windows, list_podlings lists podlings with reports, query_metric_rankings ranks podlings by metric, and search_podlings searches podling names. The descriptions unambiguously differentiate each tool's function.
All tools follow a consistent verb_noun or verb_adjective_noun pattern using snake_case: compare_windows, get_report_markdown, get_report_summary, get_window_metrics, health_overview, list_metrics, list_podlings, query_metric_rankings, and search_podlings. The naming is predictable and readable throughout, with no deviations or mixed conventions.
With 9 tools, the count is well-scoped for the Apache health reporting domain. Each tool earns its place by covering distinct aspects such as listing, retrieving, comparing, searching, and ranking podling health data. This is neither too thin nor too heavy, providing comprehensive functionality without bloat.
The tool surface offers complete coverage for querying and analyzing Apache podling health reports. It includes listing and searching podlings, retrieving raw and parsed report data, comparing across windows, getting metrics and rankings, and providing overviews. There are no obvious gaps; agents can perform full workflows from discovery to detailed analysis without dead ends.
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