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

With no annotations, the description carries the behavioral burden. It discloses what the tool returns, how leads are composed, and that include=['raw'] appends the underlying demand report. This gives an agent a solid expectation of behavior, though it does not explicitly state read-only semantics or data freshness.

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 compact, front-loaded with the core purpose, and every clause adds useful information: the rollup type, the cross signals, the lead format, and the include behavior. No filler or redundant schema repetition.

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?

Even without an output schema, the description fully describes what a caller gets: ranked leads with headline, signal, and suggested angle, plus optional raw demand report. It also clarifies the combination logic (demand map crossed with rating movement), which is enough for an agent to use the tool correctly.

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 50%; the context parameter is fully described in the schema, and the description adds meaning for include by specifying that 'raw' appends the underlying demand report. Between schema and description, both parameters are meaningfully explained without redundancy.

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 defines a specific, recognizable deliverable: a ranked weekly rollup of story leads derived from demand and rating movement. It enumerates the signal types (unmet demand, risers/fallers, hot-but-thin capabilities) and the output shape (headline, signal, suggested angle), making the tool's function unmistakable and clearly distinct from sibling tools like find_rating_movers or gap_analysis.

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 phrase 'weekly what's worth writing rollup' gives a clear editorial context and implies it should be used for content/story selection. It does not explicitly name alternatives or state when not to use it, but the description's framing is specific enough to guide an agent toward the right task.

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