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Query documentation filesystem

query_docs_filesystem_cerebrium
Read-onlyIdempotent

Run a read-only shell-like query against a virtualized, in-memory filesystem rooted at / that contains ONLY the Cerebrium 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 to head or cat — a page at the URL path /some/page lives at /some/page.mdx. To search the docs with exact keyword or regex matches, use rg. To understand the docs structure, use tree or ls.

Paths are specific to this site — never guess them. Discover real paths with tree / -L 2, ls /, or the search tool before reading. If a path does not exist, that only means the guess was wrong; it does NOT mean the topic is undocumented — use rg -il "keyword" / to find where it is covered.

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 /some-directory && ls or ls /some-directory). Do NOT assume that cd in one call affects the next call.

Examples (replace the placeholder paths with real ones from tree or search):

  • tree / -L 2 — see the top-level directory layout

  • rg -il "rate limit" / — find all files mentioning "rate limit"

  • rg -C 3 "apiKey" /some-directory/ — show matches with 3 lines of context around each hit

  • head -80 /some/page.mdx — read the top 80 lines of a specific page

  • head -80 /page-one.mdx /page-two.mdx /section/page-three.mdx — read multiple pages in one call

  • cat /some/page.mdx — read a full page when you need everything

  • cat '/openapi/https://s3.eu-west-1.amazonaws.com/www.cerebrium.ai/openapi_spec.json' | jq '.paths | keys' — list OpenAPI endpoints

OpenAPI specs for this site are mounted at: '/openapi/https://s3.eu-west-1.amazonaws.com/www.cerebrium.ai/openapi_spec.json', /openapi/package.json, /openapi/data/training-dataset-example.json. Use them to answer questions about endpoints, request/response schemas, parameters, and authentication.

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, /some/page.mdx becomes /some/page.

Input Schema

NameRequiredDescriptionDefault
commandYesA shell command to run against the virtualized documentation filesystem (e.g., `rg -il "keyword" /`, `tree / -L 2`, `head -80 /path/file.mdx`).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive/closed-world, yet the description adds substantial context beyond that: the sandbox is virtualized and in-memory, no writes/network/process control, calls are STATELESS with working directory resetting to `/`, and output is truncated to 30KB per call. The statelessness and truncation warnings are the kind of behavioral detail annotations cannot convey. Minor gap: no coverage of latency or command-failure semantics, keeping it from 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.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core purpose and bold-sectioned (Workflow, Supported commands, statelessness, examples), so it scans well. It is longer than strictly necessary — the OpenAPI mounting details and multi-example list add bulk — but nearly every section earns its place for a complex tool.

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

Completeness5/5

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

Despite no output schema, the description explains output characteristics (truncation limit, md-to-URL path conversion), command capabilities and limits, and the stateless execution model. For a single-param tool this is more than complete enough to invoke and interpret results correctly.

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

Parameters4/5

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

Schema coverage is 100% for the single `command` param, so the schema carries baseline weight. The description nonetheless enriches semantics considerably with supported-command lists, `--help` guidance, and multiple concrete command examples, though these are scattered rather than mapped per-parameter.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource ('run a read-only shell-like query against a virtualized, in-memory filesystem') and immediately scopes it to Cerebrium docs pages and OpenAPI specs. It also explicitly distinguishes itself from the sibling search tool and clarifies there is no separate get-page tool, so an agent can place it among siblings without opening schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives explicit routing: use the search tool for broad/conceptual queries, use this tool for exact keyword/regex, structural exploration, or reading a page by path. It even specifies a discovery workflow (tree/ls before reading) and the alternative when a path guess fails (rg -il). This is textbook when/when-not/alternatives guidance.

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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