generate_rag_jsonl
Convert rag-index.json content (JSON array) to rag-index.jsonl (one JSON object per line)
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| rag_index_json | Yes | String contents of rag-index.json (must be a JSON array) |
Convert rag-index.json content (JSON array) to rag-index.jsonl (one JSON object per line)
| Name | Required | Description | Default |
|---|---|---|---|
| rag_index_json | Yes | String contents of rag-index.json (must be a JSON array) |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must fully inform the agent of behavioral traits. It only describes the conversion process but omits potential side effects (e.g., whether the original file is modified, if output overwrites existing files, or if there are permissions required). This is insufficient for a risk-aware agent.
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, clear sentence that conveys the essential information without any redundancy. Every word serves a purpose, and it is appropriately 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 conversion tool with a single parameter and no output schema, the description covers the core operation and output format. It lacks details on error handling or input validation, but given the low complexity, it is largely complete.
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?
With 100% schema description coverage, the baseline is 3. The tool description does not add any additional meaning beyond the schema's parameter description; it merely restates the conversion purpose. The parameter documentation in the schema is already adequate.
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 uses a specific verb 'Convert' and identifies both the source ('rag-index.json content (JSON array)') and the target ('rag-index.jsonl (one JSON object per line)'), making the tool's function immediately clear. It distinguishes itself from sibling tools like 'generate_ai_readiness_files' by addressing a unique conversion task.
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 provides no indication of when to use this tool versus alternatives, nor does it mention any prerequisites or context. The sibling tools are unrelated, so the lack of guidance leaves an AI agent without decision-making support for selecting this tool.
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.
Each tool targets a distinct purpose: generating the full workflow, converting a specific file, retrieving specs, classification guide, instructions, or listing files. No overlapping functionality.
All tools use consistent snake_case with verb_noun structure (generate_*, get_*, list_*), making the set predictable and easy to navigate.
With 6 tools, the set covers the core informational needs (specs, guide, instructions, file list) plus the main workflow generator and a format converter, which is well-scoped for the domain.
The tool set lacks tools for actually writing or outputting the generated files; 'generate_ai_readiness_files' returns a workflow but no file creation tool exists, leaving a significant gap in the lifecycle.