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AILANG Parse

by io.github.sunholo-data
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Convert document

mcpConvert
Read-only

Create a document in another format: docx, pptx, xlsx, odt, odp, ods, html, md or qmd. To write a new document, write Markdown and send it as content with filename "notes.md" (headings become slides in pptx). To convert an existing document, give it ONE way: fileRef: a file the user uploaded (mcp-file://docparse/file_...). file: in ChatGPT, the file the user attached (ChatGPT fills it in). content + filename: the document itself; binary files base64-encoded with contentEncoding="base64", text as plain text. input: an https:// URL of a publicly reachable document, or a sample id from mcpFormats. Which way to send a file: a file in your sandbox or workspace: call createUpload (one token PER FILE; set count for several) and run its curl line, then pass the fileRef here. curl fails with a network error, or the user wants to pick a file: call uploadDocument (the user chooses it in the AILANG Parse card). The card parses the file; it does not convert or edit it. a public https:// link; short text as content. In ChatGPT, file. Never parse the file yourself (your own script, or your own reading of it) and present that as this tool's result: if the file cannot be sent, tell the user. The result carries download_url, a link to the generated file valid for one hour: give it to the user. It also carries the file as base64 in content (encoding "base64"; text formats come back as utf8).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fileNo
inputNo
apiKeyNo
contentNo
fileRefNo
filenameNo
outputPathNo
outputFormatYes
contentEncodingNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / properties / file
      Added value: +{
+  "additionalProperties": false,
+  "properties": {
+    "download_url": {
+      "type": "string"
+    },
+    "file_id": {
+      "type": "string"
+    },
+    "file_name": {
+      "type": "string"
+    },
+    "mime_type": {
+      "type": "string"
+    }
+  },
+  "required": [
+    "download_url",
+    "file_id"
+  ],
+  "type": "object"
+}
    • addedInput schema / properties / fileRef
      Added value: +{
+  "type": "string"
+}
  2. Changed4 schema fields changed
    • addedInput schema / properties / content
      Added value: +{
+  "type": "string"
+}
    • addedInput schema / properties / contentEncoding
      Added value: +{
+  "type": "string"
+}
    • addedInput schema / properties / filename
      Added value: +{
+  "type": "string"
+}
    • changedInput schema / required
      Previous value: -[
-  "input",
-  "outputFormat"
-]New value: +[
+  "outputFormat"
+]
  3. Changed1 schema field changed
    • changedInput schema / required
      Previous value: -[
-  "input",
-  "outputFormat",
-  "outputPath",
-  "apiKey"
-]New value: +[
+  "input",
+  "outputFormat"
+]
  4. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Goes well beyond the annotations: it discloses that download_url expires after one hour, that the result is also returned as base64/utf8 content, that createUpload issues one token per file, and that the card parses but does not convert. It also warns against a specific failure mode (parsing the file yourself and presenting that as the tool's result).

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-loads the core purpose and then uses structured, scannable branches; nearly every sentence carries actionable guidance. It is dense and long, but the length is driven by genuine routing complexity rather than filler.

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

Completeness4/5

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

For a 9-parameter conversion tool with no output schema, the description covers input channels and return values well (download_url plus base64/utf8 content). Auth (apiKey) and outputPath are never addressed, so it is not quite complete.

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?

With 0% schema description coverage the description must carry the load, and it does explain fileRef, file, content+filename, contentEncoding='base64', input and the outputFormat values. It leaves apiKey and outputPath unexplained, which is the only real gap.

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 and resource ('Create a document in another format') and immediately enumerates the supported target formats. It is clearly distinguishable from siblings like createUpload, uploadDocument and mcpFormats, which it explicitly routes to by name.

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?

Provides an explicit decision tree for the four input channels (fileRef, file, content+filename, input) and a 'which way to send a file' branch covering sandbox files, curl failures, user-picked files and public URLs. It also names the fallback tools (createUpload, uploadDocument) and the conditions that select them.

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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