Goldsky Docs

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and closed-world, so safety is covered; the description goes well beyond by disclosing statelessness (cwd resets to `/` every call, no variables/aliases persist), the 30KB output truncation limit, and the absence of writes/network/process control. These are exactly the operational traits an agent must know before chaining calls.

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?

It is long, but front-loaded with the core identity and organized with bolded sections (Paths, Workflow, commands, statelessness, examples) so an agent can skim to the relevant part. Nearly every sentence is operational rather than filler, though the example list and command enumeration add some bulk.

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?

There is no output schema, and the description compensates: it explains the 30KB truncation, advises targeted `rg -C`/`head -N` over broad `cat`, and tells the agent how to convert returned filesystem paths back to URL paths when citing pages. Nothing needed to call and interpret results is missing.

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, so the baseline is 3. The description adds substantial meaning beyond the schema: the `.mdx` path convention mapping URL paths to filesystem paths, the stateless cwd rule with workarounds (`&&`, absolute paths), and six concrete command examples.

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?

States a specific verb (run a read-only shell-like query) against a specific resource (a virtualized in-memory filesystem containing ONLY Goldsky documentation pages), and explicitly negates what it is not (not a real shell, not on any machine). It also distinguishes itself from the search_goldsky sibling by declaring itself the only way to read page content.

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 routes the agent: '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 never to guess paths and gives a recovery path (`rg -il "keyword" /`) when a path guess fails.

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 readOnly, idempotent, non-destructive, closed-world reads, so the safety profile is covered. The description adds value beyond that by disclosing the return shape ('contextual content with titles and direct links') and the follow-up workflow for retrieving full pages, though it says nothing about result limits, ranking, or empty-result 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?

Purpose is front-loaded in the first sentence, followed by usage conditions, return shape, and cross-tool guidance in a logical order. The parenthetical example of paths and head/cat is longer than strictly necessary but is functional, not filler.

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

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

For a one-parameter search tool with no output schema, the description covers purpose, selection criteria, return content, and the recommended follow-up path to the sibling tool. Only marginal gaps remain (pagination, ranking, or zero-result guidance), which are not critical for correct invocation.

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?

There is a single parameter with 100% schema description coverage, so the schema already carries the parameter contract and the baseline is 3. The description implies a natural-language query but adds no syntax, filtering, or format guidance beyond what the schema states.

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?

States a specific verb and resource ('Search across the Goldsky knowledge base') and enumerates the content types returned (code examples, API references, guides). It clearly distinguishes itself from the sibling query_docs_filesystem_goldsky by positioning search as discovery versus full-page reading.

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?

Gives explicit when-to-use conditions ('answer questions about Goldsky, find specific documentation, understand how features work, locate implementation details') and names the alternative tool with the exact condition that selects it and the follow-up mechanics (.mdx append plus head/cat). Nothing is left to inference.

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.