Registers explicit TCC curve points for OpenDSS datasets using provided segments and source references; it does not digitize or invent curves.
Registra puntos TCC explícitos; no digitaliza ni inventa curvas.
| Name | Required | Description | Default |
|---|---|---|---|
| shape | Yes | ||
| curve_id | Yes | ||
| revision | No | ||
| segments | Yes | ||
| dataset_id | Yes | ||
| source_url | No | ||
| source_type | Yes | ||
| time_semantics | Yes | ||
| source_reference | Yes | ||
| digitization_method | No |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses only that it does not digitize or fabricate curves, which is a data-integrity signal, but says nothing about validation behavior on the 7 required inputs, mutation side effects, permission needs, or what happens on conflicting curve_id/revision.
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?
A single short sentence, front-loaded with the action and its negative scope. Efficient, though its brevity is partly under-specification rather than disciplined concision given the tool's 10-parameter complexity.
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?
The tool has 10 parameters with zero schema coverage, no annotations, and no output schema, so the description is the only source of guidance — and it addresses none of the parameter or behavioral burden. It is far from complete for a registration tool of this complexity.
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% across 10 parameters (7 required), and the description supplies no meaning for any of them (shape, segments, time_semantics, source_type, source_reference, revision, etc.). An agent gets no guidance on the expected formats or semantics of the most consequential inputs.
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 verb (registra) and resource (puntos TCC / dataset curva TCC), and distinguishes itself from siblings like vincular_dataset_curva_tcc_p5b and evaluar_curva_tcc_p5b by clarifying it records explicit points rather than digitizing. It does not name alternatives directly, so sibling differentiation is only implicit.
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 negative constraint 'no digitaliza ni inventa curvas' implies usage context (only use when you have explicit point data, not when you need extraction), which is a useful when-not signal. However, no explicit when-to-use or positive routing to siblings such as vincular_dataset_curva_tcc_p5b is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.