Standardize markdown syntax and field values for D&D 5e spells or monsters, and optionally generate chunks for RAG indexing.
Normalize markdown formatting and standardize field values. Also generates chunks for RAG indexing.
| Name | Required | Description | Default |
|---|---|---|---|
| data | Yes | Resource data to normalize | |
| options | No | ||
| resource_type | Yes | Type of resource to normalize |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. 'Normalize' and 'standardize' imply mutation of supplied data, but it never says whether it writes back to storage or just returns a transformed payload, whether it is idempotent, or how failures are reported. That is a significant gap for a mutating tool with zero annotation coverage.
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, zero filler, front-loaded with the primary verb and resource. The only weakness is that the third capability (chunk generation) is tacked on as an aside rather than structured as a distinct mode.
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?
A mutating, multi-mode tool with nested options, no annotations, and no output schema leaves important questions open: what is returned, whether chunk generation is opt-in via options.generate_chunks or automatic, and how this differs from rag_chunk. The description stops short of what an agent needs to invoke it confidently.
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 67%, above the baseline threshold, and the description adds no parameter meaning beyond the schema — resource_type's enum, the data object, and all five options flags are documented in the schema itself. Baseline 3 is appropriate; it does not compensate for the undocumented remainder.
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?
States a specific verb (normalize/standardize) and the three things it acts on: markdown formatting, field values, and RAG chunks. However it names no sibling, which matters here because 'generates chunks for RAG indexing' overlaps with rag_chunk in the sibling list, so the agent cannot tell which to pick.
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 when-to-use guidance, no preconditions, and no alternatives. The overlap with rag_chunk is left entirely unaddressed, and it never says whether this should run before validate_entry or instead of it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.