hub_trajectory

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

With no annotations, the description carries the transparency burden. It honestly discloses that the tool is deterministic, explains the current task-count weighting and the future weighting once logd records durations, and surfaces cycle detection as a fixable output. It does not explicitly state side effects, but the read-only nature is strongly implied.

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 dense but well-structured: it front-loads the core purpose, enumerates return values compactly, and adds a useful limitation note. Every sentence contributes value without 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?

Given the lack of an output schema, the description thoroughly explains all returned concepts (ready, blocked, layers, criticalPath, cycles) and the current weighting limitation. This is sufficient for an agent to invoke the tool and interpret results.

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 schema covers the only parameter (project) with 100% coverage, and the description adds no additional parameter semantics. Since the schema already does the heavy lifting, a baseline of 3 is appropriate.

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 deterministic dependency-graph plan over tasks' depends_on, distinguishes it from an ML forecast, and names the key outputs (ready, blocked, layers, criticalPath, cycles). This uniquely identifies the tool's function and differentiates it from siblings like hub_graph and hub_task_list.

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?

Explicit usage guidance is given: 'Use to see given deps, what is the actual order / what is the critical path to a milestone.' This provides clear when-to-use context, though it does not mention when not to use it or name alternative tools.

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