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Storyflo

by io.github.Alisammour

Get my private podcast feed URL

get_my_private_feed
Idempotent

Return the caller's PRIVATE per-user podcast feed URL — a personalized daily brief (the stories from the topics the listener follows) delivered to whatever podcast app they already use (Apple Podcasts, Overcast, Pocket Casts, Snipd). This is the Substack/Patreon private-feed model: the token lives in the URL path (unguessable, fetchable over HTTPS) — paste the returned feed_url into the app's "Add a show by URL". Pass the listener's existing listener_token (from the storyflo /listen page) as identity; the private feed token is minted on first call and stable thereafter. Keep the URL private — anyone with it can subscribe. Public — the listener_token arg is the credential, no OAuth required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
listener_tokenYesThe listener's existing storyflo listener_token (identity). Get it from the /listen page or the /v1/listeners surface.

TDQS

A4.6/5.0
Behavior5/5

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

Goes far beyond the annotations: discloses the token lives in the URL path, is unguessable and fetchable over HTTPS, is minted on first call and stable thereafter, and warns that anyone with the URL can subscribe. Also clarifies the authentication model (listener_token as credential, no OAuth). This is rich behavioral context that annotations do not provide.

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 more verbose than minimal but every sentence adds value: purpose, usage, formatting, privacy warning, and credential details. The structure flows logically from what to what to how, with no filler.

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?

Given the tool's complexity (token-based auth, privacy implications, persistent minting), the description covers all essential aspects: what it returns, how to invoke it, what the credential is, the security model, and the behavior on first call. No output schema exists, but the description mentions the return value ('feed_url') sufficiently.

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

Parameters4/5

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

The schema already documents the listener_token with a description, and the description reinforces it by explaining its role as identity and where to get it. The description adds the link between the token and the minting behavior, but the schema already covers the semantics well, so this is solid but not exceptional.

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 specific verb and resource: 'Return the caller's PRIVATE per-user podcast feed URL.' It clearly distinguishes this from sibling tools like list_podcasts and get_audio_url by emphasizing the private, personalized, per-user nature and the delivery mechanism (podcast apps).

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 provides clear when-to-use context: it explains the private-feed model, how to obtain the URL, and how to use it ('paste the returned feed_url into the app's "Add a show by URL"'). It does not explicitly name alternatives or exclusion criteria, but the usage context is unambiguous.

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