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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered; the description adds that the tool returns units to draw plus per-component amounts, which is real output context. It does not mention error behavior (e.g., unknown blend name, dose exceeding vial contents) or how ambiguity in composition resolution is reported.

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?

Two sentences, front-loaded with what is computed, then the invocation rule. The parenthetical blend examples are dense but each earns its place by anchoring the tool to concrete real-world inputs.

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?

With 9 parameters, no output schema and no annotations about results, the description does the necessary work of saying what comes back (draw units, per-peptide amounts). Gaps remain around failure modes and the composition-version fallback, though the latter is documented in the schema.

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 baseline is 3, but the description goes beyond the schema by explaining the joint semantics of the two dosing modes: dose applies to targetPeptide by default or to the entire blend when totalDose is set. It also frames blend-vs-components as alternative inputs, which clarifies how those two mutually exclusive-feeling 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?

States a specific computation ('math for vials holding two or more peptides') and names the two outputs: units to draw and per-peptide amount delivered per draw. The 'two or more peptides' scope cleanly separates it from the single-peptide peptide_reconstitution_calculator sibling, and concrete blend examples (KLOW, GLOW, BPC-157 + TB-500) make the domain unmistakable.

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 a clear invocation recipe: name a known blend or list components, then supply a dose for either targetPeptide or the whole blend via totalDose. It implies the single-peptide case belongs elsewhere but never names peptide_reconstitution_calculator or peptide_supply_calculator as alternatives, so there is no explicit when-not-to-use routing.

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