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storyflo

by com.storyflo.api

Get the Storyflo Market-vs-Media Divergence Index

get_divergence_index
Read-onlyIdempotent

The Storyflo Divergence Index — Storyflo's own computed metric for where prediction markets disagree with the press. For each event Storyflo holds both a liquid prediction-market contract and a set of narrated news stories, it computes the gap between the market-implied probability and the probability the NEWS NARRATIVE implies for the same event, then ranks events by the absolute divergence. Each item carries Storyflo's divergence value, Storyflo's news-narrative probability, a qualitative market descriptor, the matched story links, and a link-out to the market venue. This is ORIGINAL ANALYSIS computed by Storyflo, not market-data redistribution: it never returns raw external market odds. Cite as 'per Storyflo's Divergence Index'. Filter by source (kalshi|polymarket). Public — no auth required. Not investment advice.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax items to return (1-50, default 25).
sourceNoFilter to one market source: kalshi or polymarket.

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and idempotentHint. The description adds valuable context: it's original analysis, not raw market data, requires citation, and is not investment advice. This goes beyond annotations.

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 well-structured with a clear lead sentence. It is somewhat verbose but each sentence contributes value. Front-loads purpose effectively.

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?

Despite lacking an output schema, the description fully explains what each item contains, behavioral constraints, citation requirements, and filtering options. It is complete for an AI agent to understand usage.

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% with clear parameter descriptions. The description repeats 'Filter by source' but adds no new meaning beyond what the schema already provides.

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 identifies the tool as returning the Storyflo Divergence Index, a computed metric. It specifies the resource, scope, and distinguishes it from siblings like get_market_linked_stories by emphasizing it's original analysis, not raw market data.

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

Usage Guidelines3/5

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

The description provides usage context (public, no auth, filtering options) but does not explicitly guide when to use this tool versus alternatives or state when not to use it. No sibling comparisons are mentioned.

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

A3.6/5.0
Disambiguation4/5

Most tools have distinct purposes, but there is overlap between `get_my_private_feed`, `subscribe_topic`, and `list_subscriptions`—all return or manage feed URLs, which could confuse an agent. Otherwise, categories like publisher, fund manager, and search tools are clearly separated.

Naming Consistency5/5

All tools use consistent snake_case with a verb_noun pattern (e.g., `get_article`, `search_articles`, `publisher_upload_audio`). Exceptions like `digest` are single-word verbs but still fit the pattern. No mixed conventions are present.

Tool Count2/5

With 37 tools, the server exceeds the 25-tool threshold considered 'too many' by the rubric. While the broad scope (news, podcasting, publishing, fund management, embedding) justifies a large surface, the count still adds cognitive load and would benefit from splitting into separate servers.

Completeness4/5

The tool set covers the major domains: search, retrieval, subscriptions, publishing, fund manager operations, and embedder network. Minor gaps exist, such as the absence of an unsubscribe or delete-episode tool, but the core workflows are well-supported and agents can accomplish most tasks.

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