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Honeydew AI Documentation

Query documentation filesystem

query_docs_filesystem_honeydew_documentation
Read-onlyIdempotent

Run a read-only shell-like query against a virtualized, in-memory filesystem rooted at / that contains ONLY the Honeydew Documentation documentation pages. 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

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.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "command": "<command>"
    },
    "name": "query_docs_filesystem_honeydew_documentation"
  }
}

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. Changed1 schema field changed
    • removedInput schema / $schema
      Removed value: -"http://json-schema.org/draft-07/schema#"
  2. Added
  3. Removed
  4. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Beyond the annotations, it discloses crucial behavior: the filesystem is sandboxed, paths are site-specific, calls are stateless, working directory resets to '/', writes/network/process control are unavailable, and output is truncated to 30KB. These details materially affect how an agent should construct and batch commands.

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?

The description is well structured and front-loaded with bolded guidance and examples, but it is lengthy and contains some repetition around the sandbox/no-real-shell behavior. It earns most of its length given the complexity, though not every sentence is strictly non-redundant.

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?

Given a one-parameter command tool with rich annotations, no output schema, and several operational constraints, the description covers everything needed: allowed commands, path discovery, stateless behavior, output limits, batching, and URL path conversion. No critical invocation guidance is missing.

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

Parameters5/5

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

Although schema coverage is 100%, the description adds substantial meaning for the single command parameter: supported utilities, constraints, path conventions, statelessness, batching guidance, and many concrete examples. This goes well beyond the schema's example text and helps the agent compose valid commands.

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?

The description states a specific verb and resource: a read-only shell-like query against a virtualized filesystem containing only Honeydew documentation. It explicitly distinguishes this from the sibling search tool and clarifies that there is no separate 'get page' tool, so an agent can select it correctly.

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?

It gives explicit routing guidance: use the search tool for broad/conceptual queries, and use this tool for exact keyword/regex matching, structural exploration, or reading full page content by path. It also prescribes a workflow and explains how to handle missing paths, leaving little to inference.

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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