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Storyflo

by io.github.Alisammour

Get crypto market exposure link (Kraken affiliate)

get_crypto_market_link
Read-onlyIdempotent

Return Storyflo's markets-partner Kraken affiliate URL for a given crypto asset (BTC, ETH, etc). Editorial linkout, not a trading prompt: the URL points at Kraken's public asset page so a listener who wants exposure can reach a regulated venue without leaving the brief context. Markets-as-INPUT posture (counsel-cleared) — Storyflo never quotes prices, never recommends positions, and never frames exposure as risk-free.

Behavior

  • Read-only. No persistent server state.

  • Idempotent — same (asset, embedder_slug) returns the same URL.

  • Fail-closed — when KRAKEN_AFFILIATE_ENABLED is off OR the partner base URL is unset, the call returns an error structure rather than a half-formed URL.

  • Attribution-aware — pass embedder_slug to credit the embedding publisher in the affiliate ?ref parameter; default falls back to ?ref=storyflo so the link is always trackable.

When to use Surface the link in show-notes copy or in MCP-client renderings of a crypto-relevant story. DO NOT inline the URL into spoken audio narration without the host-read line that frames it as an editorial signal.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
assetYesPrimary crypto asset symbol — BTC, ETH, SOL, USDC, etc. Case-insensitive; upper-cased before being embedded in the URL.
embedder_slugNoOptional embedder attribution slug. When set, the affiliate URL carries ?ref=<slug>; omit to default to ?ref=storyflo.

TDQS

A4.5/5.0
Behavior5/5

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

Beyond the annotations (readOnlyHint, idempotentHint, destructiveHint), the description discloses 'No persistent server state,' 'Fail-closed' behavior in detail, and 'Attribution-aware' behavior with the default ?ref=storyflo. It also explains that an error structure is returned rather than a half-formed URL. No contradictions with 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 structured with a purpose paragraph, a Behavior bullet list, and a When-to-use section. While somewhat long for a simple URL-returning tool, every section adds valuable context—especially the compliance-sensitive framing. It is front-loaded and avoids tautology.

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?

Despite lacking an output schema, the description clearly indicates the primary return value (a URL) and the fail-closed error structure. It covers purpose, behavior, and usage. A minor gap is the absence of the exact error response shape, but this is not critical given the tool's simplicity.

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 coverage is 100%, and schema descriptions already document asset case-insensitivity/upper-casing and embedder_slug's default ?ref=storyflo behavior. The description's Behavior section restates this without adding new parameter-specific details, so the 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 opens with a clear, specific purpose: 'Return Storyflo's markets-partner Kraken affiliate URL for a given crypto asset (BTC, ETH, etc).' It immediately distinguishes the tool from siblings by emphasizing the editorial linkout nature and 'Markets-as-INPUT' posture, and the resource (affiliate URL) is unambiguous.

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?

The 'When to use' section explicitly states usage in show notes or MCP-client renderings, and provides a clear exclusion: 'DO NOT inline the URL into spoken audio narration without the host-read line.' This is explicit contextual guidance, even naming a specific condition for 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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TDQS

A3.8/5.0
Disambiguation5/5

Every tool has a clearly distinct purpose, with detailed descriptions that prevent ambiguity. Even similar tools like search_articles, search_declassified, and search_unified target different corpora, and the publisher tools are well-separated. No overlap that would confuse an agent.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern with snake_case, using clear prefixes like get_, search_, subscribe_, publisher_, fm_, digest_, etc. The naming is predictable and systematic, making it easy for an agent to infer functionality.

Tool Count4/5

At 37 tools, the count is higher than the typical 3-15 range for a coherent set, but the server covers a wide domain (content retrieval, podcast management, fund manager book, embedder network, etc.). Each tool earns its place, though the set could be slightly reduced by merging some rare-use tools.

Completeness4/5

The tool surface is comprehensive for the server's purpose—search, audio, subscriptions, publisher workflows, and special features like the Divergence Index. Minor gaps exist (e.g., no explicit unsubscribe tool, no article update/delete), but they are not critical for core workflows.

Resources