calc_npv
COMPUTE. Net Present Value (discounted cash flow). NPV = sum(CF_t/(1+rate)^t); cashflows[0] is period 0 (usually the negative outlay).
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| rate | Yes | ||
| currency | No | ||
| cashflows | Yes |
COMPUTE. Net Present Value (discounted cash flow). NPV = sum(CF_t/(1+rate)^t); cashflows[0] is period 0 (usually the negative outlay).
| Name | Required | Description | Default |
|---|---|---|---|
| rate | Yes | ||
| currency | No | ||
| cashflows | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It discloses the period-0 convention for cashflows[0], which is a useful behavioral detail. However, it does not specify the expected rate format (decimal vs percent), how currency is handled, or error conditions.
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 a single, tightly written sentence with a formula and a key clarification. Every element is informative, with no fluff or 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?
For a simple calculation tool, the description covers the core logic but omits important context such as rate format, currency semantics, and expected output. Given no annotations and no output schema, these gaps make it only minimally viable.
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 description coverage is 0%, so the description must compensate. It adds meaning for 'rate' and 'cashflows' via the formula and the period-0 explanation. However, 'currency' is left completely unexplained, and the rate's unit (decimal vs percent) is not clarified.
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 the tool computes Net Present Value using the provided formula, naming the exact operation and resource. It distinguishes itself from sibling tools like calc_irr and calc_compound_growth by specifying the discounted cash flow method.
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?
No guidance is provided on when to use this tool versus alternatives such as calc_irr or calc_compound_growth. There is no mention of typical use cases, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have clear, distinct purposes across three namespaces (calc_, decide_, sim_) plus composites. Some conceptual overlap exists (e.g., decide_sensitivity vs. sim_sensitivity, decide_score vs. decide), but descriptions clarify the boundaries well.
Names follow a consistent snake_case convention with a namespace prefix (calc_, decide_, sim_) and a descriptive verb_noun structure. Even composite tools and utilities like health_check and list_capabilities fit the pattern.
24 tools is on the heavier side, but it's justified for a meta-server exposing three distinct engines plus cross-domain composites. The count is appropriately scoped for the breadth of capabilities advertised.
The set covers all core domains with discovery (list_capabilities, *_list_*), health_check, and composite tools linking simulation to decision and valuation. Minor gaps include lack of a template management tool, but sim_run accepts free-form models, mitigating this.