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Fodda Deep Research

by ai.fodda

generate_visual

Read-onlyIdempotent

Create a presentation-ready data visualization from research findings. Available chart types: "cultural_shifts" (From→To transitions), "competitive_compass" (brands on 2 axes), "trend_constellation" (network of related trends), "implication_ladder" (Signal→Trend→So What→Do What), "innovation_pathway" (Now→Near-Term→Future), "opportunity_map" (2×2 white space analysis). Returns a branded SVG that renders directly in the chat. Highlight focal entity using top-level "focus":"Name" or per-item "focus":true.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesJSON string containing chart data. Optional top-level "focus":"Name" or per-item "focus":true highlights key entity in brand accent. cultural_shifts: {shifts:[{from,to}]}. competitive_compass: {brands:[{name,x,y,focus?:boolean}], axes:{left,right,top,bottom}, focus?:string}. trend_constellation: {trends:[{name,x,y,focus?:boolean}], connections:[{from,to,strength}], focus?:string}. implication_ladder: {signal,trend,so_what,do_what}. innovation_pathway: {now,near_term,future}. opportunity_map: {items:[{name,consumer_desire,market_activity,focus?:boolean}], x_label?:string, y_label?:string, focus?:string}
chart_typeYesThe type of visualization to generate

TDQS

A4.2/5.0
Behavior4/5

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

The annotations already mark the tool as read-only, idempotent, and non-destructive, and the description adds useful behavioral context beyond that: it returns a branded SVG that renders directly in chat and supports focus highlighting. This explains the user-visible output and customization behavior without contradicting the annotations.

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

Conciseness5/5

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

The description is dense but well-organized: the core purpose leads, the available chart types are enumerated compactly, and the output format plus focus option are stated in the final sentence. Every sentence contributes necessary decision-making or invocation information without padding.

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

Completeness4/5

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

For a tool with two required parameters, a complex nested data string, and no output schema, the description covers chart-type choices, data schemas, focus highlighting, and return format. It does not mention error cases or constraints like SVG size limits, but the provided guidance is sufficient for correct invocation in most cases.

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 100%, and the input schema already documents each chart type's expected data structure in detail. The description adds interpretive value for chart selection and focus semantics, but most parameter meaning is already present in the schema, so the added semantic uplift is moderate.

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

Purpose5/5

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

The description opens with 'Create a presentation-ready data visualization from research findings,' which names a specific verb, resource, and context. It then enumerates all six chart types and states the output is a branded SVG, making the tool's function unmistakable and distinct from the non-visualization sibling tools.

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

Usage Guidelines4/5

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

The description clearly conveys when to use this tool: whenever a presentation-ready visual from research findings is needed, with a catalog of supported chart types matching different analytical needs. It does not explicitly state when not to use it or name alternative sibling tools, but the usage context is sufficiently clear.

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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TDQS

A4.2/5.0
Disambiguation4/5

Most tools have clearly distinct roles: graph discovery, graph search, node detail, neighbor mapping, evidence retrieval, deep research launch, and status polling are all identifiable. The main ambiguity is between search_graph and get_label_values(label='Trend') for listing trends, and between deep_research_topic's built-in supplemental coverage and get_supplemental_context.

Naming Consistency4/5

The set largely follows a snake_case verb_noun pattern such as search_graph, list_graphs, get_node, read_url, and generate_visual. The outlier is deep_research_topic, which is noun-led rather than verb-led, and get_my_account is a minor deviation from the pure verb_noun pattern, but neither seriously disrupts usability.

Tool Count5/5

14 tools is well-scoped for a deep-research platform: graph discovery, graph search, retrieval, evidence, supplemental data, status polling, visualization, URL ingestion, and account/capability helpers all earn their place. The set feels like a deliberate pipeline rather than a miscellany.

Completeness4/5

The research lifecycle is well covered: discover graphs, search, explore trends, get supporting evidence, add supplemental data, launch deep research, poll status, and generate visuals. Minor conveniences like canceling or listing past research sessions are missing, but there are no dead ends for the core workflow.

Resources