learn_posts
Ideas people posted to Trana Learn and the reviewer accepted, newest first, as feed cards (id...
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | ||
| limit | No |
Ideas people posted to Trana Learn and the reviewer accepted, newest first, as feed cards (id...
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | ||
| limit | No |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, non-destructive and openWorld, so safety is covered. The description adds genuine behavior beyond that: results are restricted to reviewer-accepted ideas and ordered newest first, which tells an agent exactly what it will and will not see.
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?
It is short and front-loaded, but it is truncated rather than concise — an unfinished clause is a structural defect, not economy. An agent reading it cannot tell whether the missing text contained essential detail.
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?
With no output schema, 0% schema coverage on two parameters, and a truncated description, key facts an agent needs (what 'id' scopes, what 'limit' caps, what a 'feed card' contains) are absent. The ordering and acceptance filter are the only substantive completeness wins.
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 neither 'id' nor 'limit' is documented anywhere, and the description does not compensate. Worse, the fragment '(id...' suggests parameter discussion was intended but is cut off, so an agent has no idea whether 'id' filters a single post or paginates from a cursor.
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 does identify a specific resource and a meaningful scope: ideas posted to Trana Learn that a reviewer accepted, ordered newest first. However, the sentence is visibly truncated mid-parenthetical ("as feed cards (id..."), which leaves the intended explanation of the return shape unfinished and makes the purpose harder to trust at a glance.
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 call this versus the obvious sibling learn_post (which presumably creates such an idea) or trana_feed/trana_proposals. The 'reviewer accepted' qualifier hints at a curation boundary but is never framed as a use condition or exclusion.
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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