hwp_table_to_json
Extracts a table from a HWP document by index and returns its data as JSON for structured processing.
Instructions
표 데이터를 JSON 형식으로 추출합니다.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| table_index | Yes | 표 인덱스 |
Extracts a table from a HWP document by index and returns its data as JSON for structured processing.
표 데이터를 JSON 형식으로 추출합니다.
| Name | Required | Description | Default |
|---|---|---|---|
| table_index | Yes | 표 인덱스 |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, and the description only states it extracts data. It does not disclose whether it is read-only, destructive, requires authentication, or any side effects. The description fails to compensate for 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 very short (one sentence), which is concise but lacks structure. It does not front-load key information or use formatting to aid scanning. It is not verbose but could benefit from more detail.
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 has a single parameter, no output schema, and no annotations, the description is insufficiently complete. It does not cover error scenarios, return format, or limitations. The agent may need additional context to use it reliably.
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?
The schema coverage is 100%, so the baseline is 3. The description does not add any additional meaning to the single parameter (table_index) beyond what the schema already provides. No extra clarification on how to obtain the index.
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 (extract) and resource (table data) and output format (JSON). It distinguishes itself from sibling tools like hwp_table_to_csv by specifying JSON output, but does not explicitly contrast with all table-related 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?
No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, context, or exclusions. The agent must infer usage from the description alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/gmlcjf0326/claude-code-hwp-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server