analyze_compatibility

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does this well by stating that the tool uses graph-based detection and returns a numerical compatibility score range, which tells the agent both the approach and what kind of result to expect. It does not detail error handling or invalid-tech-id behavior, but the core behavior is transparent.

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: the first states the core function, the second defines the output scale. Both sentences earn their place, and the most important information is front-loaded. There is no fluff or 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 tool with a single required parameter and a clear output scale, the description provides nearly everything needed to invoke it correctly. The input schema covers parameter semantics, and the description communicates the result format. A minor gap is the lack of an explicit example of the returned structure, but the scoring range largely compensates.

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 input schema already fully documents the only parameter, tech_ids, with an example. The description adds no additional parameter-level detail, such as format constraints or relationship to the scoring scale. Baseline 3 is appropriate because schema coverage is 100% and the description doesn't need to compensate.

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 a specific action ('Analyze compatibility between technologies') and identifies the method ('graph-based synergy/conflict detection'). It also defines the output format with a concrete scoring scale (+3 to -3), making the tool's purpose unmistakable and distinct from siblings like compare_tech or recommend_stack.

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 gives no explicit guidance on when to use this tool versus alternatives such as compare_tech, map_integrations, or recommend_stack. It implies usage through its purpose, but with many sibling tools offering related functionality, the lack of explicit selection criteria is a notable gap.

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