List recent class journal entries (date descending) for YOUR account.
Args:
mcp_token: Your personal VenuVidya token — GET /api/auth/mcp-token
while signed in to the app. Scopes results to your journal only.
level: optional level filter.
limit: max number of classes (1-100, default 20).
| Name | Required | Description | Default |
|---|---|---|---|
| level | No | ||
| limit | No | ||
| mcp_token | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full behavioral disclosure burden. It does disclose ordering (date descending) and scoping (YOUR account), and explains the token requirement. However, it does not mention potential errors (e.g., invalid token, rate limits) or whether the operation has any side effects beyond reading. This is adequate but not fully transparent.
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 concise and well-structured. It opens with a one-line summary, then breaks parameters into an 'Args:' list with each on its own line. No fluff, no repetition. Every sentence serves a purpose.
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?
In the absence of an output schema, the description does not explain what fields each class entry contains, nor does it mention error behavior or pagination beyond the limit parameter. For a simple list tool this is acceptable, but the gaps around return format and failure modes leave the agent somewhat under-informed.
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 0%, so the description must compensate. It does so effectively: mcp_token is explained with an acquisition method and scoping, limit is given a range and default, and level is identified as an optional filter. The only gap is that level does not enumerate possible values, but overall the parameter explanations add meaning well beyond the bare schema.
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 opens with a specific verb-resource phrase: "List recent class journal entries (date descending) for YOUR account." It clearly identifies the action (list), the target (class journal entries), and a distinguishing scope (YOUR account). This is enough to set it apart from sibling tools like list_lessons or get_class without ambiguity.
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 implies when to use the tool (when you need your own recent class entries) but does not explicitly state alternatives or exclusion criteria. There is no mention of 'use instead of list_lessons' or 'not for other users' accounts.' The guidance is implicit rather than explicit, so it earns a 3.
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 has a clearly distinct purpose: ask_venuvidya is a RAG chatbot, search_syllabus is keyword search, list/get_lesson and list/get_class handle distinct resources, and log_practice_session writes practice data. No two tools have overlapping responsibilities.
All tools follow a consistent verb_noun pattern in snake_case (ask, get, list, log, search). Even 'ask_venuvidya' uses a verb + proper noun, matching the style. Naming is predictable and scannable.
Seven tools cover the core flows of a study guide: browsing lessons, searching content, logging practice, and retrieving class journals. This is well-scoped—not too sparse, not bloated.
The surface covers viewing lessons and classes, searching, and logging practice, but lacks write operations for lessons or classes (e.g., annotating or updating). However, the server's role is a study guide, and the missing operations are not essential for its stated purpose.