Retrieve an application's retro or learning plan from a job-hunting campaign to review past feedback and prepare for the next interview.
Read an existing retro/learning plan for an application
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Application slug | |
| campaign | Yes | Campaign name (e.g. "default") |
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 behavioral burden. It implies a safe read but says nothing about what happens if no retro exists, permission requirements, or what is returned — significant gaps for a tool whose entire job is retrieval.
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?
A single tight sentence with the resource and scope front-loaded; nothing is wasted, though it is arguably too terse given the missing behavioral context.
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 parameter-light read tool with full schema coverage this is minimally adequate, but with no annotations and no output schema the description could still say what a retro contains or when one is available. It is complete enough to invoke but not to anticipate results.
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 100%, so both parameters (slug, campaign) are already documented in the schema. The description's 'for an application' only loosely echoes the slug parameter and adds no format or constraint detail, so baseline 3 is correct.
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 (read) and resource (retro/learning plan) scoped to an application, so the agent knows what it does. However, it does not distinguish itself from close siblings like append_retro or aggregate_retros, and the 'retro/learning plan' phrasing leaves the resource name slightly ambiguous.
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 prerequisites, and no mention of alternatives such as aggregate_retros for summaries or append_retro for writes. The agent must infer the context entirely.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.