Finds the minimum vertex cover of a graph using exact bitmask enumeration for up to 20 vertices, taking vertex count and edge pairs as input.
Find the minimum vertex cover of a graph using exact bitmask enumeration (up to 20 vertices).
| Name | Required | Description | Default |
|---|---|---|---|
| edges | Yes | Edges as [u, v] pairs | |
| vertex_count | Yes | Number of vertices (max 20) |
Changes observed during successful MCP inspections.
v0.1.11Does 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 algorithmic approach (exact bitmask enumeration) and the size constraint (20 vertices), which is meaningful behavioral context. But it doesn't state whether the result is optimal, what the return format is, or the failure mode for oversized graphs.
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 sentence that front-loads the purpose and immediately qualifies the computational limit. No wasted words.
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 moderately complex algorithm tool with no annotations and no output schema, the description covers purpose and scale but omits key details like output format (list of vertices vs cover size), failure behavior beyond 20 vertices, and whether the graph is treated as undirected. Adequate but with clear gaps.
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 coverage is 100%, so the schema already documents both parameters including the vertex_count max. The description adds no syntax or format details beyond what the schema provides. Baseline 3 is appropriate when the schema does the heavy lifting.
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 (Find) and resource (minimum vertex cover of a graph) and distinguishes itself from algorithm siblings by naming the exact method (bitmask enumeration). An agent can tell this apart from max_independent_set or graph_coloring immediately.
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 parenthetical 'up to 20 vertices' implies the domain of applicability, which is useful guidance. However, it doesn't explicitly say when to use this vs alternatives like approximation algorithms, nor does it state what happens for larger graphs (error? different tool?).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.