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

Annotations already cover the safety profile (readOnly, idempotent, closed-world, non-destructive), and the description adds genuine behavioral context on top: the two-stage mechanics, the Gordon Growth terminal, and the warning that results are highly sensitive to discount and terminal rates and should be treated as a single point rather than an answer. It also discloses that outputs will not reconcile with the internal model, preventing a false-cross-check failure.

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?

Front-loaded with what the tool computes, then routing, then caveats — a sensible order with no filler. The third paragraph's framing ('This computes your assumptions, it does not endorse them') is slightly rhetorical but conveys a real limitation about interpreting a single result.

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?

There is no output schema, and the description compensates by naming all three returned values. Combined with the units-and-range detail in the schema and the safety annotations, an agent has everything needed to call this correctly and interpret the result.

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% with per-parameter units, ranges and the discount-rate-above-terminal-rate constraint already documented, so the schema carries most of the load. The description still adds relational meaning the schema cannot: growth_rate applies over growth_years and then handsoff to terminal_growth_rate in perpetuity, which clarifies how two parameters interact.

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 first sentence names a specific verb (runs a two-stage DCF), the exact inputs it operates on (numbers you provide), and the three outputs (fair value per share, margin of safety, terminal-stage share of value). It also explicitly distinguishes itself from get_stock_valuation and its fade-based model, so an agent can separate the two without opening either schema.

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?

Gives three concrete use cases (value under user assumptions, sensitivity testing, checking a DCF's arithmetic) and an explicit exclusion: do not use to look up Zyberno's own valuation. The alternative tool is named and the reason for divergence is explained, which is exactly the routing information an agent needs.

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