docs_append_textAdd text to the end of a Google Doc. Use when insertion position doesn't matter.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to append | |
| document_id | Yes | Document ID |
| Name | Required | Description | Default |
|---|---|---|---|
| error | No | Error code if connection failed | |
| message | No | Error message if connection failed | |
| replies | No | Results of batch update requests | |
| documentId | No | Document ID |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Output schema / (root)Previous value: -nullNew value: +{
+ "description": "Response from appending text to end of document",
+ "properties": {
+ "documentId": {
+ "description": "Document ID",
+ "type": "string"
+ },
+ "error": {
+ "description": "Error code if connection failed",
+ "type": "string"
+ },
+ "message": {
+ "description": "Error message if connection failed",
+ "type": "string"
+ },
+ "replies": {
+ "description": "Results of batch update requests",
+ "type": "array"
+ }
+ },
+ "type": "object"
+}Input schema / examplesAdded value: +[
+ {
+ "document_id": "1BxiMVs0XRA5nFMKUVfGo6Q6XcYBCy_N1LCcFrZkZecc",
+ "text": "\n\nNext steps: Review and approve by end of week."
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare write operation and idempotency. Description adds that text goes to the end, but does not disclose auth needs or output format.
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?
Single sentence, no wasted words, purpose 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 append tool with full schema and output schema, description is sufficient. Provides usage guidance.
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 covers 100% of parameters with descriptions. Description adds no extra parameter details beyond schema.
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?
Description clearly states verb 'Add', resource 'Google Doc', and scope 'to the end'. Distinguishes from siblings like docs_insert_text.
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 says 'Use when insertion position doesn't matter', implying context. But does not name sibling tools or state when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Several tools are nearly indistinguishable: ask_pipeworx and ask_pipeworx_beta are explicitly identical in behavior, while ask_pipeworx_grounded and deep_research heavily overlap with the same router. The dense Polymarket tool cluster and discovery tools (discover_tools vs suggest_questions) further blur boundaries, though many individual tools do have distinct niches.
Names are consistently lowercase snake_case, which helps, but the convention is mixed: some are verb_noun (docs_create, list_subscriptions), some are noun phrases (entity_profile, deep_research, bet_research), and one uses a suffix (ask_pipeworx_beta). It is readable but not a predictable pattern across the set.
37 tools is already above the 25+ threshold, but the bigger problem is that the server is named Google_docs and only 6 of the 37 tools relate to Google Docs. The remaining 31 tools form a broad data-research and prediction-market platform, making the set feel bloated and mislabeled for its apparent purpose.
For a Google Docs server, the surface is incomplete: you can create, read, insert, replace, and append text, but there is no delete, no list/search, no formatting control, and no permission handling. The extensive Pipeworx and Polymarket tools cover a different domain entirely, so they do not fill the gaps in the docs workflow.