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Fodda Topic & Trend Research

by ai.fodda

list_graphs

Read-onlyIdempotent

List all expert knowledge graphs the user can access — IDs, descriptions, authors, sectors, signal counts, and topic coverage (e.g. retail, tech, food, travel, fashion, beauty, sports). Use FIRST in any session to discover available sources before searching. Returns graph metadata needed for graphId parameters in other tools.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
userIdNoOptional user identifier. Authenticated users are identified automatically via API key. For trial users, this helps track usage.

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds useful context by listing the specific metadata returned and confirming that only accessible graphs are listed, going beyond what annotations provide.

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?

Two sentences, front-loaded with the core action and result fields, followed by usage guidance. Every sentence contributes value with zero redundancy.

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

Completeness5/5

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

For a simple list tool with one optional parameter and no output schema, the description adequately covers what is returned, when to use it, and how it relates to the rest of the toolset. It is self-sufficient for correct invocation.

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?

The single optional parameter (userId) is fully described by the schema at 100% coverage. The description adds no new parameter semantics; the schema already explains optionality and authentication, so baseline 3 is appropriate.

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 clearly states the tool lists all expert knowledge graphs the user can access, enumerates the returned fields (IDs, descriptions, authors, sectors, signal counts, topic coverage), and distinguishes it from sibling search tools by positioning it as the discovery step.

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

Usage Guidelines5/5

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

Explicitly instructs to use 'FIRST in any session to discover available sources before searching' and explains that returns graph metadata needed for graphId parameters in other tools, creating clear when-to-use and relationship-to-siblings guidance.

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

All Fodda Topic & Trend Research toolsInspect
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TDQS

A4.3/5.0
Disambiguation4/5

The tools are mostly distinct: search_graph, search_insights, search_statistics, and get_supplemental_context are carefully differentiated by output type, and graph exploration/evidence tools have clear roles. A couple of retrieval tools (get_validated_trends vs search_graph, search_statistics vs get_supplemental_context) could be mistaken at a glance, though their descriptions do enough to separate them.

Naming Consistency5/5

All tool names use a consistent lowercase snake_case verb_noun pattern (search_*, get_*, list_*, generate_*, check_*, read_*). Verbs map predictably to actions, and there are no mixed conventions or vague generic names.

Tool Count5/5

Fifteen tools is at the upper edge of the ideal range but each one maps to a distinct research workflow step: discovery, graph search, targeted retrieval, evidence, supplemental data, visualization, and account/capability checks. The breadth is justified by the server's broad trend-research scope.

Completeness5/5

The surface covers the full read-only research lifecycle: list graphs, search across them, drill into nodes/neighbors/evidence, get quantitative and qualitative answers, supplement thin coverage with external data, and produce visuals. Meta tools for account/capability and URL import prevent dead ends.

Resources