list_jobsRecover recent solver jobs after losing conversation context and retrieve up to 100 jobs, newest first, to restore traceable Ottosim run history.
Recover recent solver jobs after losing conversation context. Returns up to 100 jobs, newest first.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| jobs | Yes |
Changes observed during successful MCP inspections.
v0.3.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare read-only, idempotent, non-destructive, open-world behavior. The description adds useful behavioral detail beyond annotations: it returns at most 100 jobs and orders them newest first. It does not explain truncation or what happens if more than 100 jobs exist.
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?
Two short sentences with zero waste. The use case is front-loaded, followed immediately by the return volume and ordering.
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 zero-parameter tool with rich annotations and an output schema, the description covers the essential context: when to use it, how many jobs come back, and in what order. An agent can invoke it correctly without further description.
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?
The tool has zero parameters, so the baseline is 4. The description correctly adds no parameter semantics because there are none to explain.
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 states a specific resource (recent solver jobs) and a clear recovery use case, distinguishing it implicitly from single-job tools like inspect_job. It is clear but does not explicitly name or contrast with sibling tools.
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?
It gives a clear triggering scenario: 'after losing conversation context.' However, it does not state when not to use it or explicitly name alternatives such as inspect_job for detailed job inspection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.