Altss Documentation

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), yet the description adds substantial extra behavior: statelessness with working directory resetting to `/` on every call and no carry-over of variables/history, a 30KB truncation limit, an enumerated command whitelist, and an explicit 'no writes, no network, no process control' constraint. It even corrects a likely failure mode (a nonexistent path means a wrong guess, not an undocumented topic).

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 and organized with bolded section labels (Workflow), an examples block, and batching/truncation guidance, so an agent can scan it quickly. Minor redundancy exists, e.g. the path-guessing warning is restated and the example list is broader than strictly needed, which keeps it from a 5.

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?

With no output schema, the description still covers what the agent needs: output truncation at 30KB, how to keep reads targeted (`rg -C`, `head -N`), batching multiple reads in one call, and how to convert returned filesystem paths back to URL paths for the user response. Nothing material about correct invocation is left out.

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 `command` string parameter and the schema already describes it at 100% coverage, so the baseline would be a 3. The description earns above baseline by adding real semantics the schema cannot express: the `.mdx` path convention (`/some/page` -> `/some/page.mdx`), the supported command list, a `--help` affordance, and concrete example invocations. It stops short of a 5 only because much of that guidance is workflow framing rather than parameter-level detail.

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: 'Run a read-only shell-like query against a virtualized, in-memory filesystem rooted at `/`'. It immediately scopes the resource ('contains ONLY the Altss Data & Agent Docs documentation pages') and negates the obvious wrong interpretation ('This is NOT a shell on any real machine'). This clearly separates it from the sibling `search_altss_data_agent_docs`.

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 routing: 'Start with the search tool for broad or conceptual queries... 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 resolves a likely confusion up front by stating 'there is no separate get page tool' and mapping that need onto `head`/`cat`.

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 and closed-world, so the safety profile is covered. The description adds genuinely new behavior: results include titles and direct links, and the follow-up workflow (append .mdx, head/cat the path). It stops short of noting result-count limits or ranking behavior, so not a 5.

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 and each subsequent sentence carries distinct information (when to use, what comes back, escalation path). The parenthetical example is slightly verbose but functionally useful, 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?

No output schema exists, so the description's explanation of the return shape (contextual content with titles and links) and the chained retrieval pattern is exactly what an agent needs. Everything required to call it and act on results is present.

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?

Only one parameter with 100% schema coverage, so the baseline is 3. The description does not clarify query syntax (natural language phrase vs keywords, quoting, filters), which is the one thing that would add value beyond the schema's 'Search query'.

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 (search) and resource (Altss Data & Agent Docs knowledge base) plus the content types returned (code examples, API references, guides). It implicitly differentiates from the sibling query_docs_filesystem tool by being the discovery step rather than the full-content retrieval step.

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 triggers (answer questions, find specific docs, understand features, locate implementation details) and an explicit alternative with the condition that selects it: use query_docs_filesystem to head/cat a page when full content is needed. 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.