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apex_add_metric_cards

Add KPI metric cards to Oracle APEX pages. Each card displays a value from a SQL query with customizable label, icon, color, and style options like gradient, flat, or outline.

Instructions

Add styled KPI metric cards (gradient/flat/outline). Each metric: label + sql + icon + color.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
styleNoVisual style: - "gradient": Colored gradient background with white text (default) - "white": White card with colored accent border - "dark": Dark card with neon accentgradient
columnsNoNumber of columns in the card grid (2, 3, 4, or 6).
metricsYesList of metric definitions. Each dict supports: - "label": Display label (required, e.g., "Pacientes Ativos") - "sql": SQL query returning a single value (required, e.g., "SELECT COUNT(*) FROM TEA_BENEFICIARIOS WHERE FL_ATIVO='S'") - "icon": Font Awesome icon class (e.g., "fa-users", "fa-chart-bar") - "color": Color theme: "blue" | "green" | "orange" | "red" | "purple" | "teal" | "indigo" | "amber" (auto-assigned if omitted) - "prefix": Text before value (e.g., "R$", "$") - "suffix": Text after value (e.g., "%", "pts") - "subtitle": Optional secondary text under the value - "link_page": Page number to link to on click (optional) Example: [ {"label": "Pacientes Ativos", "sql": "SELECT COUNT(*) FROM TEA_BENEFICIARIOS", "icon": "fa-users", "color": "blue"}, {"label": "Taxa de Conclusão", "sql": "SELECT ROUND(AVG(NR_PCT_TOTAL)) FROM TEA_AVALIACOES", "icon": "fa-check-circle", "color": "green", "suffix": "%"}, ]
page_idYesTarget page ID.
sequenceNoRegion display order on the page.
region_nameYesRegion title (hidden by default).
color_paletteNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

Annotations are all false, indicating a mutation but not destructive. The description adds little behavioral context beyond 'add' – no mention of region creation, page impact, or side effects. With many similar tools, this lack of transparency makes selection harder.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that efficiently conveys the core function. It is concise and front-loaded, but so brief that it omits differentiation and usage context, though the schema carries much of the detail.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (7 params) and a large sibling family, the description is too sparse to provide complete context. It relies heavily on the schema and does not explain when to choose this over related components like apex_add_kpi_row.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 86%, so the schema already documents most parameters. The description merely restates that each metric includes label, sql, icon, and color, which is already in the schema, adding marginal value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a clear verb ('Add') and resource ('styled KPI metric cards'), and specifies key attributes (gradient/flat/outline, label+sql+icon+color). However, it does not explicitly distinguish from sibling tools like apex_add_kpi_row or apex_add_spotlight_metric, so it loses a point.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to use this tool versus alternatives, which is problematic given the many add_* siblings. It does not mention use cases, prerequisites, or when not to use it.

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

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