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Storyflo

by io.github.Alisammour

Stream briefing render events (SSE)

stream_briefing_render_events
Read-onlyIdempotent

Subscribe to real-time briefing-render events. Returns the SSE endpoint URL with the chosen filters as query params — the agent's MCP client should open it with EventSource (browser), httpx.stream / aiohttp (Python), or curl -N (CLI). Event types: briefing.rendered (daily-brief lands), declassified.published (new Declassified episode), persona_briefing.rendered (persona brief synthesised / audio rendered). Frame shape: {event_type, seq, slug, vertical, persona_slug, audio_url, published_at, metadata}. The endpoint replays the last ~1000 events on connect; a heartbeat is emitted every 30s. Public-anon read.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
verticalNoOptional vertical filter.
event_typeNoOptional event_type filter.

TDQS

A4.5/5.0
Behavior5/5

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

Beyond annotations, the description discloses the SSE endpoint URL behavior, event types, frame shape, the ~1000-event replay on connect, the 30-second heartbeat, and public-anonymous read access. This is rich behavioral context that annotations do not cover.

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 compact, well-structured, and front-loaded with the core purpose. Each sentence delivers useful information: client usage, event types, frame shape, replay, heartbeat, and auth.

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 streaming tool with no output schema, the description fully covers return shape, event semantics, connection behavior, and client options. It is self-sufficient and leaves little ambiguity.

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 schema covers both parameters fully with descriptions and an enum for event_type. The description adds that filters are passed as query params, but this is a minor addition since schema coverage is 100%.

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 it subscribes to real-time briefing-render events and returns an SSE endpoint URL. It specifies the concrete event types and distinguishes this streaming tool from the sibling getter 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?

Provides explicit guidance on how to consume the endpoint: 'the agent's MCP client should open it with EventSource (browser), httpx.stream / aiohttp (Python), or curl -N (CLI)'. It does not explicitly contrast with polling or sibling tools, but the real-time subscription use case is 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

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