docs
Server Details
Search and query nTop's knowledge base and engineering guides from AI applications.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 4.5/5 across 3 of 3 tools scored.
Each tool serves a distinct purpose: filesystem query for reading/searching docs, semantic search for broader queries, and feedback submission. No overlap in functionality, making it easy for an agent to select the correct tool.
Tool names follow a verb_noun pattern but vary in length and inclusion of the product name 'nTop' (e.g., 'query_docs_filesystem_n_top' vs. 'search_n_top' vs. 'submit_feedback'). While still readable, the inconsistency in suffix is a minor deviation.
With 3 tools, the server is slightly minimal but still scoped well. The filesystem tool is powerful and covers many use cases, justifying the low count. It's not over or under-scoped enough to cause issues.
The tool set covers all essential documentation needs: reading any page, keyword/regex search, structural exploration, semantic search, and feedback. No obvious gaps exist for the stated purpose of a documentation server.
Available Tools
3 toolsquery_docs_filesystem_n_topARead-onlyIdempotentInspect
Run a read-only shell-like query against a virtualized, in-memory filesystem rooted at / that contains ONLY the nTop documentation pages and OpenAPI specs. This is NOT a shell on any real machine — nothing runs on the user's computer, the server host, or any network. The filesystem is a sandbox backed by documentation chunks.
This is how you read documentation pages: there is no separate "get page" tool. To read a page, pass its .mdx path (e.g. /quickstart.mdx, /api-reference/create-customer.mdx) to head or cat. To search the docs with exact keyword or regex matches, use rg. To understand the docs structure, use tree or ls.
Workflow: Start with the search tool for broad or conceptual queries like "how to authenticate" or "rate limiting". Use this tool when you need exact keyword/regex matching, structural exploration, or to read the full content of a specific page by path.
Supported commands: rg (ripgrep), grep, find, tree, ls, cat, head, tail, stat, wc, sort, uniq, cut, sed, awk, jq, plus basic text utilities. No writes, no network, no process control. Run --help on any command for usage.
Each call is STATELESS: the working directory always resets to / and no shell variables, aliases, or history carry over between calls. If you need to operate in a subdirectory, chain commands in one call with && or pass absolute paths (e.g., cd /api-reference && ls or ls /api-reference). Do NOT assume that cd in one call affects the next call.
Examples:
tree / -L 2— see the top-level directory layoutrg -il "rate limit" /— find all files mentioning "rate limit"rg -C 3 "apiKey" /api-reference/— show matches with 3 lines of context around each hithead -80 /quickstart.mdx— read the top 80 lines of a specific pagehead -80 /quickstart.mdx /installation.mdx /guides/first-deploy.mdx— read multiple pages in one callcat /api-reference/create-customer.mdx— read a full page when you need everythingcat /openapi/spec.json | jq '.paths | keys'— list OpenAPI endpoints
Output is truncated to 30KB per call. Prefer targeted rg -C or head -N over broad cat on large files. To read only the relevant sections of a large file, use rg -C 3 "pattern" /path/file.mdx. Batch multiple file reads into a single head or cat call whenever possible.
When referencing pages in your response to the user, convert filesystem paths to URL paths by removing the .mdx extension. For example, /quickstart.mdx becomes /quickstart and /api-reference/overview.mdx becomes /api-reference/overview.
| Name | Required | Description | Default |
|---|---|---|---|
| command | Yes | A shell command to run against the virtualized documentation filesystem (e.g., `rg -il "keyword" /`, `tree / -L 2`, `head -80 /path/file.mdx`). |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint. The description adds substantial behavioral context: it is a virtual sandbox (not a real shell), no writes or network, stateless per call, working directory resets, output truncated to 30KB. It also clarifies that 'cd' does not persist between calls. This goes far beyond what annotations provide.
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?
Although lengthy, the description is well-structured with sections, bullet points, and examples. It front-loads the essential purpose and compares to the sibling tool, then dives into details. Every sentence provides necessary information without redundancy. It is as concise as possible given the 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 the tool has a single parameter, no output schema, and is a read-only query tool, the description covers all relevant aspects: command syntax, statelessness, truncation, output conversion to URLs for references. It is complete for an agent to use effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'command' has a detailed description in the schema (100% coverage). The description further enriches meaning by listing supported commands, providing usage examples, and specifying constraints like output truncation and stateless behavior. This adds significant value beyond the schema 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 tool's purpose: running read-only shell-like queries against a virtualized documentation filesystem. It explicitly distinguishes from the sibling tool 'search_n_top' by specifying that this tool is for exact keyword/regex matching, structural exploration, or reading full page content, while 'search_n_top' is for broad or conceptual queries. The verb 'query' and resource 'docs filesystem' are specific and unique.
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 explicit when-to-use guidance, contrasting this tool with the sibling 'search_n_top'. It recommends starting with the search tool for broad queries and using this tool for exact matches, structural exploration, or reading specific pages. It also states the stateless nature and command chaining requirements, making usage clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_n_topSearch documentationARead-onlyIdempotentInspect
Search across the nTop knowledge base to find relevant information, code examples, API references, and guides. Use this tool when you need to answer questions about nTop, find specific documentation, understand how features work, or locate implementation details. The search returns contextual content with titles and direct links to the documentation pages. If you need the full content of a specific page, use the query_docs_filesystem tool to head or cat the page path (append .mdx to the path returned from search — e.g. head -200 /api-reference/create-customer.mdx).
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Search query |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint. The description adds context about the return format ('contextual content with titles and direct links') and directs to another tool for full content, which aligns with annotations. No contradictions.
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 relatively concise with a clear front-loaded statement of purpose. It provides necessary usage guidance and return information without excessive verbiage. Slightly longer than ideal, but each sentence adds 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?
Given the tool's simplicity (one required parameter, no output schema, and rich annotations), the description covers all necessary aspects: purpose, usage scenarios, return content, and references to a sibling tool for deeper needs. It is 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?
Schema coverage is 100% with a single 'query' parameter described as 'Search query.' The description reinforces the purpose but does not add additional parameter details beyond the schema. 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 'Search across the nTop knowledge base to find relevant information, code examples, API references, and guides.' It specifies the action (search), the resource (nTop knowledge base), and the scope, distinguishing it from sibling tools like query_docs_filesystem.
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 this tool when you need to answer questions about nTop, find specific documentation...' and provides a clear alternative: 'If you need the full content of a specific page, use the query_docs_filesystem tool.' This covers both when to use and when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
submit_feedbackSubmit documentation feedbackAInspect
Report a problem with this documentation site so the docs team can fix it. Use when a documentation page is incorrect, outdated, confusing, incomplete, or has a broken example. This is for feedback about the documentation content itself — not for product support requests or feedback about this tool or assistant.
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | The documentation page path the feedback is about (e.g., the page you were reading, such as `/quickstart`). | |
| feedback | Yes | A clear description of the documentation issue or suggestion — what is incorrect, outdated, missing, or confusing. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint=false, destructiveHint=false, openWorldHint=true, idempotentHint=false. Description does not add extra behavioral context beyond purpose, such as whether feedback is anonymous or logged. For a simple feedback tool, it is adequate but lacks additional depth.
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?
Description is a single concise paragraph with two front-loaded sentences: first states purpose, second provides usage guidelines. No wasted words.
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 (2 string parameters, no output schema, no nested objects), the description adequately covers purpose and usage. It could mention expected outcome (e.g., feedback is submitted successfully), but is largely 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?
Schema coverage is 100% with detailed descriptions for both parameters. The description does not add new semantics beyond restating purpose. Baseline 3 is appropriate as schema already covers 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 clearly states it reports problems with the documentation site. It specifies the verb 'report' and resource 'documentation site', and distinguishes from sibling tools by noting it is for documentation content feedback, not product support or tool feedback.
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 states when to use: for incorrect, outdated, confusing, incomplete, or broken example documentation. Also states when not to use: not for product support requests or feedback about the tool/assistant.
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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