trace-mcp

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

With no annotations provided, the description carries full burden for behavioral disclosure. It implies a read-only operation by describing what it 'shows', but doesn't explicitly state it's non-destructive or has no side effects. It mentions the output includes 'how much institutional knowledge is captured' which adds some behavioral context about the tool's analytical purpose, but lacks details about response format, data freshness, or any limitations.

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 perfectly concise at two sentences. The first sentence efficiently lists all key output metrics (total decisions, active/invalidated counts, breakdowns by type and source). The second sentence adds valuable context about institutional knowledge capture. Every word earns its place with zero waste.

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 parameterless tool with no output schema, the description provides adequate coverage of what information will be returned. It specifies multiple dimensions of statistical data (counts, breakdowns, institutional knowledge metrics). However, without annotations or output schema, it doesn't clarify the exact format of the response or whether there are any limitations on data scope or freshness.

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 0 parameters with 100% schema description coverage, so the baseline is 4. The description appropriately doesn't discuss parameters since none exist, and instead focuses on what the tool returns. This is efficient and correct for a parameterless tool.

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 clearly states the tool provides an 'overview of the decision knowledge graph' with specific metrics like total decisions, active/invalidated counts, and breakdowns by type and source. It distinguishes itself from sibling tools like 'get_decision_timeline' or 'query_decisions' by focusing on statistical summaries rather than timeline data or querying capabilities. However, it doesn't explicitly mention it's a read-only statistical report tool.

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 provides no guidance on when to use this tool versus alternatives like 'get_decision_timeline' or 'query_decisions'. It doesn't mention prerequisites, timing considerations, or what situations warrant retrieving statistical overviews versus detailed decision data. The agent must infer usage from the purpose alone.

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