A stdio MCP proxy for WeCom's official robot-doc backend that enables LLM agents to read, create, and edit WeCom documents and smartsheets with ergonomic output transforms.
Document Management
Read: Fetch full content of a WeCom doc or smartsheet as Markdown, auto-detecting the URL type (wecom_read_doc, wecom_get_doc_content)
Create: Create new documents (type 3) or smartsheets (type 10) by name, receiving back a URL and docid (wecom_create_doc)
Edit: Write Markdown content (headings, lists, tables, bold, italic) to an existing document via docid or URL (wecom_edit_doc)
Smartsheet Management
Navigation: List all sheets (sub-tables) within a smartsheet, retrieving their IDs and titles (wecom_smartsheet_get_sheet)
Field inspection: Retrieve column definitions including field names, types, and IDs (wecom_smartsheet_get_fields)
Schema setup: Initialize a smartsheet's column layout before adding data (wecom_smartsheet_setup_fields)
Record reading: Fetch all rows with structured, unwrapped cell data and ISO 8601 timestamps (wecom_smartsheet_get_records)
Record writing: Append rows using plain {column_name: value} dicts with automatic cell format conversion (wecom_smartsheet_add_records)
Ergonomic Transforms (applied automatically)
Cell unwrapping: Flattens nested smartsheet cell formats into plain scalars (_rows view)
Timestamp conversion: Converts 13-digit ms-epoch timestamps to ISO 8601 format
Enhanced error reporting: Human-readable _error_summary and _error_hint for Chinese error codes to aid troubleshooting
The server dynamically fetches and proxies all 25 tools from the WeCom backend, converting HTTP-based communication to stdio for broader MCP client compatibility.
Provides document CRUD operations for WeCom (Enterprise WeChat) Docs and Smartsheets, including creating, reading, and editing documents and structured tables via the @wecom/cli API.
⚠️ Archived 2026-08-18 — read this first
Unmaintained, and never published to PyPI. The
pip install wecom-docs-mcp-serverline further down does not work and never did — install from source if you still want to run it.Why it's archived
This server is a stdio proxy over WeCom's robot-doc MCP backend. Tencent's investment has visibly moved to a different surface: the official
WecomTeam/wecom-cli(Rust; rewritten for v1.1.0 on 2026-08-17, 14 service domains) plus the officialWecomTeam/wecom-unifiedagent skill. The robot-doc MCP backend has had no public update since 2026-04-22.What the official CLI now covers
Verified against
@wecom/cliv1.1.0 on 2026-08-18:
This project's selling point
Status in v1.1.0
stdio transport
Obsolete — the CLI is a local process. Any agent that can run a shell needs no MCP layer at all.
ms-epoch → ISO 8601
Obsolete — the CLI returns
2026-08-17 12:17:25directly.Chinese error hints
Obsolete — the CLI returns
help_message+help_instruction, including a clickable authorization-repair link.Schema passthrough
Obsolete — every subcommand accepts
--schema(full JSON Schema with field descriptions) and--doc.Smartsheet cell unwrap
Still unsolved. v1.1.0 still returns
values[field] = [{"type":"text","text":...}], and long rich-text cells fragment into dozens of segments.If you came here to give an agent access to WeCom documents
Use the official CLI, not this:
npm install -g @wecom/cli npx skills add WecomTeam/wecom-unified -y -g wecom-cli auth initThe one part still worth copying
wecom_doc_mcp/transforms.py— the cell-unwrap transform. ~120 lines, no MCP dependency. Lift it as a post-processing filter on CLI output rather than running this server.Two empirical findings worth keeping
Observed 2026-07 against the robot-doc backend:
get_doc_contentandsmartsheet_get_*use independent permission scopes. The same bot can read a smartsheet viasmartsheet_get_records(errcode 0) and still get851003 no authorityfromget_doc_contenton that same document. Route reads by document type; one working scope proves nothing about the other.Pass the full document
urlincluding?scode=rather than reconstructingdocid. The backend resolves the URL; stripping prefixes by hand yields301085 invalid docid.
An ergonomic stdio MCP facade over WeCom's official robot-doc MCP backend. It proxies all 25 backend tools verbatim and adds a transform layer that makes the raw output usable by LLM agents:
Schema passthrough — the tool list is fetched from the backend at startup, so it auto-tracks official updates. Zero schema maintenance.
Cell unwrap — smartsheet values[field] = [{"type":"text","text":...}] cells become plain scalars (in a _rows view).
ms → ISO — 13-digit ms-epoch timestamps (create_time, update_time) convert to ISO 8601.
Chinese error hints — errcode 851003 etc. get _error_summary + _error_hint so the agent learns the fix, not just the code.
Relationship to the backend: This server requires the official robot-doc MCP backend (an apikey from WeCom admin → 智能文档机器人 → API). It is a thin proxy + ergonomics layer, not a replacement.
Related MCP server: google-suite-mcp
The official robot-doc backend is an HTTP (StreamableHttp) MCP server. Two friction points: (1) many MCP clients and dev workflows prefer stdio; (2) its raw output is agent-hostile — nested cell format, ms-epoch strings, opaque error codes. This server bridges both:
official robot-doc | this server | |
Transport | HTTP (StreamableHttp) | stdio |
Tool schema | raw 25 tools | same 25, passthrough |
Cell format |
| unwrapped scalars ( |
Timestamps | ms-epoch strings | ISO 8601 |
Error codes |
| + Chinese summary + fix hint |
apikey | required | required (proxied) |
Python 3.9+
A WeCom 智能文档机器人 (Smart Doc Bot) with its API key — available to enterprises (≥10 members) via WeCom admin → 应用管理 → 智能文档机器人 → API.
⚠️ Never published to PyPI.
pip install wecom-docs-mcp-serverreturns 404. Source install is the only path.
Clone + editable:
git clone https://github.com/Beltran12138/wecom-docs-mcp-server
cd wecom-docs-mcp-server
pip install -e .Variable | Required | Description |
| yes | robot-doc apikey |
| no | override backend URL (default |
claude_desktop_config.json){
"mcpServers": {
"wecom-doc": {
"command": "wecom-docs-mcp-server",
"env": { "WECOM_MCP_APIKEY": "your_apikey_here" }
}
}
}All 25 backend tools are exposed verbatim (fetched live at startup). By domain:
Domain | Read | Write |
doc | get_doc_content | create_doc, edit_doc_content, upload_doc_image, upload_doc_file |
smartsheet (智能表) | get_sheet, get_fields, get_records | add/update/delete × sheet/fields/records |
sheet (电子表格) | get_info | add_sub, delete_sub, update_range_data, append_data |
smartpage (智能页面) | get_export_result | create, export_task |
Permission model (empirically observed 2026-07):
get_doc_contentandsmartsheet_get_*use independent permission scopes. A bot may read a smartsheet viasmartsheet_get_records(errcode 0) yet get851003 no authorityfromget_doc_contenton the same doc. Route reads by doc type.
Applied automatically on every tools/call response:
_rows on smartsheet_get_records — a flattened view where cells are unwrapped to scalars and top-level record fields (record_id, create_time, …) are preserved. The original records array is kept intact.
ms → ISO on all successful dict payloads — 13-digit ms-epoch strings → ISO 8601. Alphanumeric IDs (q979lj) are untouched.
_error_summary + _error_hint on any non-zero errcode — Chinese explanation + concrete fix.
Read a smartsheet end-to-end:
User: read https://doc.weixin.qq.com/smartsheet/s3_xxx?scode=yyy
Agent:
1. smartsheet_get_sheet(url=...) → sheet_id (e.g. "q979lj")
2. smartsheet_get_fields(sheet_id, url) → field schema (types, IDs)
3. smartsheet_get_records(sheet_id, url) → records + _rows (cells unwrapped, timestamps ISO)Pass the full
url(with?scode=) rather than guessingdocid— the backend resolves it. Manually extracting docid by stripping prefixes is error-prone (empirically:301085 invalid docid).
errcode | meaning | fix |
851000 | 文档链接有误 | check url + scode, or use docid |
851002 | 文档类型与工具不兼容 | smartsheet → use |
851003 | 无文档权限 | smartsheet 用 |
851008 | 缺文档内容读取权限 | 企微后台 → 机器人 → API 权限 |
301085 | 无效 docid | 用完整 url 含 scode |
40058 | 参数缺失 | smartsheet 需 sheet_id（先 get_sheet） |
Project | Focus |
official robot-doc MCP | backend (HTTP, ≥10 人企业) |
bot messaging via webhook | |
this server | robot-doc stdio proxy + ergonomics |
pip install -e ".[dev]" # or: pip install pytest httpx
pytest25 unit tests cover SSE/JSON parsing, ms-timestamp normalization, cell unwrap, error humanizing, and server routing/post-processing — all offline (httpx mocked).
MIT
Create a new WeCom document or smartsheet. Returns url and docid — save the docid for subsequent edits.
| Name | Required | Description | Default |
|---|---|---|---|
| doc_name | Yes | Document name (max 255 chars) | |
| doc_type | Yes | 3 = regular document, 10 = smartsheet |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It indicates the tool is a create operation (non-destructive) and provides essential output info. However, it does not mention any side effects, auth requirements, or error conditions, which is a gap given the lack of annotations.
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?
The description is a single, concise sentence that communicates purpose and key output. It is front-loaded with the action and resource.
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?
Given the tool is simple with two required params, no nested objects, and no output schema, the description covers the creation purpose and output. However, it lacks workflow guidance (e.g., how to use docid with sibling tools) and does not explain return format details.
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%, so the schema already documents both parameters. The description adds that docid is for subsequent edits, but does not elaborate on the meaning of doc_name or doc_type beyond the schema. A score of 3 is appropriate as per guidelines.
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 creates a new WeCom document or smartsheet, specifying the two types via doc_type. It distinguishes this from siblings like wecom_edit_doc and wecom_read_doc by using the verb 'create' and mentioning the output (url and docid).
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 implies usage for creation tasks and instructs to save the docid for subsequent edits, suggesting a common workflow. However, it does not explicitly state when not to use this tool or compare with alternatives such as wecom_edit_doc for modifications.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Write Markdown content to a WeCom document. Supports headings, lists, tables, bold, italic. Use docid (preferred) or url to identify the document.
| Name | Required | Description | Default |
|---|---|---|---|
| content | Yes | Markdown content to write | |
| docid | No | Document docid from wecom_create_doc (preferred) | |
| url | No | Document URL (fallback if docid unavailable) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states the tool writes content but does not disclose if the operation is destructive (overwrites vs appends), whether it requires special permissions, or what happens if the document does not exist. This is a significant gap for a mutation tool.
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?
Two sentences, no filler. The first sentence states the action, the second provides necessary detail on supported syntax and identification methods. Efficient and clear.
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?
Given no output schema and no annotations, the description could benefit from mentioning return behavior (e.g., success confirmation, errors). The tool has 3 params, one required, and current description covers identification but not the write behavior (overwrite vs append) or effects on existing content.
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 coverage is 100%, and description adds value by explaining that 'docid' is preferred and 'url' is a fallback, which clarifies their relative importance beyond the schema descriptions.
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 verb 'Write' and resource 'Markdown content to a WeCom document', and lists supported syntax (headings, lists, tables, bold, italic). However, it does not explicitly distinguish itself from sibling tools like wecom_read_doc or wecom_get_doc_content, though the action is different.
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 mentions using docid (preferred) or url to identify the document, which gives some guidance. But it does not explain when to use this tool over alternatives, e.g., when to edit vs create (wecom_create_doc) or read (wecom_read_doc).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Fetch the full content of a WeCom online doc as Markdown. Uses async polling internally.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Document URL | |
| task_id | No | Polling task_id (omit on first call) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description mentions 'Uses async polling internally', disclosing behavioral trait beyond what the schema provides (which only lists parameters). Without annotations, this is valuable. It also implies the tool may return partial results initially.
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?
Two sentences, concise and front-loaded with the purpose. The second sentence adds behavioral context. No waste.
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?
Given no output schema and no annotations, the description could be improved by mentioning the return format (Markdown) and any limits. However, it covers the main purpose and polling nature adequately.
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 coverage is 100%, so the schema already documents both parameters. The description adds that task_id is for polling and implies it should be omitted on first call, but this is already in the schema description. So baseline 3.
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 'Fetch the full content of a WeCom online doc as Markdown', which is a specific verb ('Fetch') and resource ('WeCom online doc'). It also distinguishes from siblings like wecom_read_doc likely by focusing on full content and Markdown format.
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 says 'Uses async polling internally', which implies it is for getting full content and may require an initial call with just url and then polling with task_id. However, it does not explicitly state when to use this vs siblings or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Read a WeCom document or smartsheet. Returns content as Markdown. Auto-detects URL type: /smartsheet/ URLs return table data, /doc/ URLs return document content.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Full WeCom doc or smartsheet URL (include scode param if present) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; the description carries full burden. It discloses auto-detection of URL type and return format (Markdown). However, it does not mention potential errors, rate limits, or whether authentication is needed. Still, for a read tool, this is adequate.
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 essential. No fluff, front-loaded with purpose, then adss specific behavior about return format and URL auto-detection.
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?
Given only one parameter, no output schema, and no annotations, the description is relatively complete. It explains input, behavior, and output. Could mention pagination or limitations for large docs, but overall sufficient.
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% (the url parameter is described). The description adds meaning beyond the schema by explaining what URLs are accepted and how they are processed (auto-detect). It could be more precise about the scode parameter, but minimal.
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 reads a WeCom document or smartsheet and returns content as Markdown. It distinguishes itself from siblings (e.g., wecom_get_doc_content, wecom_smartsheet_get_records) by focusing on reading with Markdown output and URL auto-detection.
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 does not explicitly state when not to use this tool vs. siblings, but it does provide context on URL types (smartsheet vs. doc) and what to expect. Implicitly, if the user wants raw data or specific fields, other tools might be better, but this is not stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Append rows to a smartsheet. Each record is a plain {column_name: value} dict — cell format conversion is handled automatically.
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | Smartsheet URL | |
| docid | No | Smartsheet docid | |
| sheet_id | Yes | Sheet ID | |
| records | Yes | List of {column_name: value} objects |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full burden. It correctly states mutation ('Append rows') but does not disclose potential side effects, error behaviors (e.g., row limit, duplicate handling), or authentication requirements. The automatic format conversion is mentioned, which is a behavioral trait, but more could be said.
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?
The description is two sentences: first defines purpose, second clarifies input format. No wasted words. Could be slightly more structured (e.g., bullet points for prerequisites), but it is efficient and 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?
Given the tool's moderate complexity (4 parameters, no output schema, no annotations), the description covers the key action and input format but lacks details on error cases, rate limits, or what happens on success. It is adequate but not comprehensive.
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 coverage is 100%, so parameters are described in the schema. The description adds value by explaining the records parameter format ('plain dict') and that cell conversion is automatic, which is not in the schema. The other parameters (url, docid, sheet_id) are already clear from schema descriptions.
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 action ('Append rows to a smartsheet') and the input format ('Each record is a plain {column_name: value} dict'). It distinguishes from sibling tools like wecom_smartsheet_get_records (read) and wecom_smartsheet_setup_fields (schema setup). The scope of operation is explicit.
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 implies use when you need to add data to an existing smartsheet, but does not explicitly state when not to use it (e.g., for creating new sheets or updating existing records) or mention alternatives among siblings. It provides no prerequisites or context about required identifiers.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get column definitions (field names, types, IDs) for a smartsheet sheet.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Smartsheet URL | |
| sheet_id | Yes | Sheet ID |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full burden. It correctly states 'Get column definitions', indicating a read operation. However, it does not disclose any behavioral traits such as pagination, performance, or authentication requirements.
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, front-loaded with the action and resource. No unnecessary words.
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?
Given the simple nature and good schema coverage, the description is adequate but could include what happens if a sheet doesn't exist or if parameters are invalid.
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 coverage is 100% and the schema already provides descriptions. The description adds no extra meaning beyond what the schema gives.
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 starts with the verb 'Get' and specifies the resource 'column definitions for a smartsheet sheet', clearly distinguishing it from siblings like wecom_smartsheet_add_records and wecom_smartsheet_get_records. It also lists the content: field names, types, IDs.
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?
No guidance on when to use this tool vs alternatives (e.g., wecom_smartsheet_get_sheet or wecom_smartsheet_setup_fields). The description implies it is for reading metadata, but does not explicitly state when to choose this over other sheet-related tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Fetch all rows from a smartsheet sheet. Returns structured row data.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Smartsheet URL | |
| sheet_id | Yes | Sheet ID |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It lacks details on read-only nature, pagination, authorization requirements, or rate limits. The word 'Fetch' implies read, but no explicit safety guarantee.
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?
Short and to the point with two sentences. No redundant information, but could be improved by front-loading the core action more clearly.
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?
Given no output schema and no annotations, the description is incomplete. It doesn't explain what 'structured row data' includes, how errors are handled, or whether results are paginated. For a fetch operation, return format is crucial.
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% with both parameters having descriptions. However, the description adds no extra meaning beyond the schema—no format or usage hints for url or sheet_id.
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 'Fetch all rows from a smartsheet sheet' with the verb 'Fetch' and resource 'rows from a smartsheet sheet', and distinctively mentions 'all rows' versus sibling tools like 'wecom_smartsheet_get_fields' which fetches fields.
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?
No guidance on when to use this tool versus siblings like 'wecom_smartsheet_get_sheet' (which likely returns sheet metadata) or 'wecom_smartsheet_add_records'. The description only says what it does, not when to prefer it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List all sheets (sub-tables) in a WeCom smartsheet. Returns sheet IDs and titles.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Smartsheet URL |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that it returns IDs and titles, which is helpful. Since no annotations are provided, the description carries the full transparency burden. It lacks detail about potential side effects (none expected for a list operation), permissions, or pagination. But it correctly implies a read-only operation.
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?
The description is a single sentence that is concise and directly states the tool's purpose and return value. No superfluous words; it earns its place.
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 listing tool with one parameter and no output schema, the description is adequate but minimal. It doesn't explain the format of the return (e.g., whether it's a list of objects) or any limitations. It lacks contextual completeness about potential errors or prerequisites.
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 coverage is 100%, with one parameter 'url' having a description 'Smartsheet URL'. The description does not add new meaning beyond the schema; it just reiterates that it lists sheets. With high schema coverage, the baseline is 3, and there is no extra parameter context added.
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 purpose: listing sheets in a WeCom smartsheet and returning their IDs and titles. It uses the specific verb 'list' and identifies the resource (sheets/sub-tables). However, it does not differentiate this tool from siblings like wecom_smartsheet_get_fields or wecom_smartsheet_get_records, which might list other entities.
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 implies when to use this tool: when you need to discover available sheets and their IDs. However, it does not provide explicit guidance on when not to use it or mention alternatives like wecom_smartsheet_get_fields for columns or wecom_smartsheet_get_records for data.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Initialize a smartsheet's column schema. Renames the default field and adds remaining fields. Must be called before adding records to a new sheet.
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | Smartsheet URL (or use docid) | |
| docid | No | Smartsheet docid (or use url) | |
| sheet_id | Yes | Sheet ID from wecom_smartsheet_get_sheet | |
| field_names | Yes | Column names in order |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description indicates it renames the default field and adds fields, hinting at destructive or setup behavior. However, no annotations are provided, so the description carries the full burden. It lacks details on reversibility, idempotency, or what happens if called on an already-initialized sheet, which is a gap for a setup action.
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?
The description is extremely concise: two sentences that cover purpose, action, and prerequisite. No wasted words.
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?
Given 4 parameters (2 required) and no output schema, the description provides basic setup context but omits details like what the default field is renamed to, error handling, or return value. The note about ordering is helpful but not comprehensive.
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%, so the schema already documents all parameters. The description does not add meaning beyond the schema; 'field_names' purpose is clear from context. Baseline 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 initializes a smartsheet's column schema by renaming the default field and adding remaining fields. The verb 'Initialize' and resource 'column schema' are specific, and the setup nature distinguishes it from read/record siblings.
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 explicitly states the tool must be called before adding records to a new sheet, giving clear temporal guidance. However, it does not mention when not to use this tool versus alternatives like wecom_smartsheet_get_fields, so it is not a full 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v1.0.0wecom_create_docwecom_edit_docwecom_get_doc_contentwecom_read_docwecom_smartsheet_add_recordswecom_smartsheet_get_fieldswecom_smartsheet_get_recordswecom_smartsheet_get_sheetwecom_smartsheet_setup_fieldsScored across 9 tools
Tools are mostly distinct: docs (create, edit, get, read) vs smartsheets (add_records, get_fields, get_records, get_sheet, setup_fields). However, wecom_get_doc_content and wecom_read_doc overlap in purpose (both fetch content), though read auto-detects smartsheets, creating slight ambiguity.
All tools follow wecom_verb_noun pattern, but verbs vary (create, edit, get, read, add, setup). Consistent snake_case and prefix, but 'get' vs 'read' for similar operations is a minor inconsistency.
With 9 tools covering document and smartsheet operations, the count is well-scoped. Each tool serves a clear purpose without redundancy, appropriate for the domain.
Covers core CRUD for docs (create, edit, read) and smartsheets (schema, records, sheets). Missing delete/update for smartsheets or document deletion, but essential workflows are complete, so minor gaps.
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