Normalize malformed Markdown bold syntax in LLM responses, converting broken asterisks into correctly formatted headers for consistent scripture output.
Normalizes LLM response text, fixing broken bold asterisk syntax ('** 2. **Header' -> '2. Header').
| Name | Required | Description | Default |
|---|---|---|---|
| markdown_text | Yes | Raw Markdown text to sanitize |
Changes observed during successful MCP inspections.
v2.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full responsibility for disclosing behavior. It clearly states the normalization behavior and illustrates it with an example. It does not discuss edge cases or side effects, but for a simple text transformation tool, the description adequately reveals what happens.
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?
A single sentence that front-loads the core purpose and includes a helpful, specific example. Every word earns its place; there is no filler or redundant restating of the tool name.
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 one-parameter transformation tool with no output schema, the description covers the input and the transformation. It does not explicitly state the return value (sanitized Markdown), but that is strongly implied by the name and description. The example clarifies the expected output format sufficiently.
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 input parameter is already documented. The description adds a transformation example but does not introduce any additional parameter semantics beyond what the schema provides. This matches the baseline for fully-covered schemas.
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 states a specific verb ('Normalizes') and resource ('LLM response text') and gives a concrete before/after example of the broken bold asterisk syntax it fixes. This clearly distinguishes it from all sibling tools, which are biblical content retrieval tools rather than text-formatting utilities.
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 indicates this is used to clean up LLM-generated Markdown, which implies post-processing scenarios. No explicit exclusions are given, but since no sibling tool performs similar sanitization, there is no real alternative to confuse it with. The usage context is reasonably clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.