Stats: format, cue count, duration, chars.
Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.
{
"id": 1,
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"arguments": {
"content": "<content>"
},
"name": "subtitle_stats"
}
}| Name | Required | Description | Default |
|---|---|---|---|
| content | Yes |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full disclosure burden, and it reveals only the metric names. It is silent on whether the call is read-only, what happens with malformed or non-subtitle input, and whether output is structured or free text.
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 with no filler, but it is a bare noun-list fragment rather than a front-loaded sentence, so the reader gets metrics before learning what the input is.
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?
No output schema exists, so the description should at least sketch the return shape; it only names four fields. Combined with the unexplained 'content' parameter and absent annotations, the definition is too thin for reliable invocation.
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 0% and the single required parameter 'content' is never explained — the description doesn't say it must be raw subtitle text in a supported format (SRT/VTT) or whether a file path is accepted. This is the main ambiguity an agent would hit.
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 fragment 'Stats: format, cue count, duration, chars' implies a subtitle statistics extractor, but never states a verb or that the resource is subtitle content. The returned metrics hint at the domain, yet an agent must infer the tool operates on subtitle files rather than plain text.
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 indication of when to use this versus text_count (plain text) or estimate_tokens, nor any prerequisites about input format. Sibling names are listed but none are referenced or excluded.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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