Cerebrium Docs

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The annotations already state readOnlyHint=true, openWorldHint=false, idempotentHint=true, and destructiveHint=false. The description adds substantial behavioral context beyond that: the filesystem is a sandbox, each call is stateless with the working directory resetting to `/`, output is truncated to 30KB, there are no writes/network/process control, and missing paths only mean the guess was wrong—not that the topic is undocumented. This fully discloses practical behavioral constraints.

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 long, the description is densely packed with necessary information and is well structured: purpose, path rules, workflow, supported commands, statelessness, examples, OpenAPI mounts, output limits, and response formatting. Every sentence earns its place, and the most critical guidance is front-loaded before examples.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-parameter shell-like tool with no output schema, this description is exceptionally complete. It covers how to read pages, how to search, how to handle missing paths, stateless behavior, output truncation, OpenAPI spec locations, and even how to convert paths back to URLs when responding to the user. An agent has everything it needs to invoke and interpret the tool correctly.

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% for the single `command` parameter, but the description adds enormous semantic value on top of the schema. It enumerates supported commands, gives concrete examples with placeholders, explains path-to-URL conversion, shows how to chain commands with `&&`, and demonstrates use of the mounted OpenAPI specs with `jq`. The parameter gains far more meaning than the schema alone provides.

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 opens with a specific verb and resource: 'Run a read-only shell-like query against a virtualized, in-memory filesystem rooted at `/`' that is explicitly limited to Cerebrium documentation and OpenAPI specs. It clearly distinguishes this tool from the sibling search_cerebrium by framing it as the way to read actual pages, not just search, and even notes there is no separate 'get page' tool.

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 an explicit workflow: 'Start with the search tool for broad or conceptual queries' and 'Use this tool when you need exact keyword/regex matching, structural exploration, or to read the full content of a specific page by path.' It also warns against guessing paths and tells the agent to use `tree` or `rg` first, covering both when to use and how to use the tool effectively.

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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds valuable behavioral context: it discloses that search returns only titles and direct links, not full content, and explains how to retrieve full content via a sibling tool. This goes beyond the annotations and helps the agent predict the output format.

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 paragraph but is well-structured: it opens with the purpose, then usage guidance, then what the search returns, and finally a pointer to the sibling tool. It is slightly long but every sentence adds value, and the critical usage guidance is front-loaded. It is not overly verbose.

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 search tool with simple parameters and clear annotations, the description is complete: it states what the tool does, when to use it, what it returns, and how to proceed for full content. It does not describe pagination or result limits, but those are minor and not essential for correct invocation. The output format (titles and links) is sufficient.

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% (both query and version are described in the schema). The description does not add parameter-specific details beyond what the schema provides, so the baseline of 3 is appropriate. The description's mention of the .mdx suffix is not about parameters but about follow-up actions, which is already covered elsewhere.

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 verb ('Search') and resource ('Cerebrium knowledge base'), and clearly enumerates what it finds (information, code examples, API references, guides). It explicitly differentiates from the sibling query_docs_filesystem by noting that search returns links and not full content, so an agent can immediately distinguish the two 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 explicitly states when to use the tool ('when you need to answer questions about Cerebrium...') and provides a concrete alternative for full content (use query_docs_filesystem to head/cat the page). It even explains the .mdx path convention, leaving no ambiguity about when to switch tools.

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?

Annotations already convey that this is a write operation (readOnlyHint=false, idempotentHint=false), and the description adds meaningful context: feedback is routed to the docs team and is scoped to documentation content. It stops short of describing what happens after submission (e.g., whether a confirmation is returned, whether it creates an issue), but it does not contradict the annotations and provides useful behavioral framing.

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 sentences, all informative. The first sentence states the purpose, the second gives concrete usage criteria, and the third excludes non-documentation feedback. No filler or redundancy; the most important information is front-loaded.

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 two-parameter tool with no output schema, the description and schema together cover the essential information: what to submit, which page, what kind of feedback, and when to use it. The only minor gap is the lack of detail about the post-submission result or confirmation behavior, which is not critical but would make it fully complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, and the parameter descriptions already explain 'path' (URL path without .mdx extension) and 'feedback' (clear description of the issue). The tool description reinforces the kind of feedback expected but adds no technical semantics beyond the schema, so the baseline score of 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 function: 'Report a problem with this documentation site so the docs team can fix it.' It identifies the specific resource (documentation site) and the action (reporting a problem), and it distinguishes itself from the sibling query/search tools by being feedback-oriented. It also explicitly carves out what it is not for: product support or feedback about the tool/assistant.

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 gives explicit when-to-use guidance: 'Use when a documentation page is incorrect, outdated, confusing, incomplete, or has a broken example.' It also provides a clear when-not-to-use boundary: 'not for product support requests or feedback about this tool or assistant.' This is strong, actionable usage direction.

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