ketan_get_ctg

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses the output type (Mermaid diagram), the contents of the graph (every tool call, checkpoint, failure, rollback with causal edges), and suggests pasting into mermaid.live for visualization. This gives meaningful behavioral context, though it does not explicitly state read-only safety or potential side effects, which are minor for a get tool.

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 two sentences long, front-loaded with the primary purpose. The second sentence adds valuable context about the graph's content and provides actionable advice (paste into mermaid.live). Every word earns its place with no redundancy.

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 no-argument tool with an output schema, the description is nearly complete: it explains what the tool does, what the output represents, and how to visualize it. The only gap is lack of explicit guidance on when to use it compared to sibling tools, but that falls under usage guidelines. The tool's simplicity and clear purpose make the description sufficient.

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 adds no parameter semantics since there are none to describe, and no additional parameter information is needed.

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?

Description states 'Get the Causal Trace Graph (CTG) as a Mermaid diagram' – clearly identifying the verb (get), resource (CTG), and output format. It also explains the content of the CTG (live DAG with tool calls, checkpoints, failures, rollbacks), which distinguishes it from sibling diagnostic tools like get_status or get_checkpoints.

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?

Description provides context that the CTG is a live DAG showing causal edges, implying it should be used for understanding causal relationships. However, it does not explicitly state when to use this tool versus alternatives like explain_failure or session_summary, nor does it mention any exclusions or prerequisites. This is only implied usage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.