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stremio_auto_fetch_subtitle

Fetches hash-matched OpenSubtitles subtitles for a video using URL or hash/size, then adds them to Stremio via add_subtitle.

Instructions

Fetch a hash-matched OpenSubtitles result and serve it through add_subtitle.

Pass a playable video_url while Stremio desktop is running so its server calculates the hash, or provide video_hash and video_size directly.

Input Schema

NameRequiredDescriptionDefault
seasonNo
episodeNo
imdb_idYes
filenameNo
languageNoeng
video_urlNo
video_hashNo
video_sizeNo
result_indexNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.0

TDQS

B3.2/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the desktop-running prerequisite and the hash calculation behavior, which is useful. However, it omits critical operational details: whether this is a read-only fetch or a mutating operation, what happens if no hash match is found, how result_index selects among multiple matches, error conditions, and rate limits. For a tool that auto-fetches and serves content, these gaps leave the agent with insufficient transparency.

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 two short sentences, front-loaded with the primary action and followed by the conditional usage instruction. It avoids verbose preamble and uses a clear imperative structure. Minor improvement possible by explicitly naming the alternative parameter path with more precision, but the size is appropriate for the task.

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

Completeness3/5

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

The tool has 9 parameters, no annotations, and an output schema exists (so return value explanation is not needed). The description covers the two main invocation modes but leaves out key operational details: prerequisites for hashing, handling of missing or ambiguous matches, and the role of result_index. Given the parameter count and zero schema coverage, more completeness is expected, though the core workflow is communicated.

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

Parameters2/5

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

Schema description coverage is 0%, meaning none of the 9 parameters have descriptions in the schema. The description explains the relationship between video_url and video_hash/video_size, and implies imdb_id is required for lookup. But it does not explain season/episode semantics, filename usage, language defaults, result_index behavior, or how video_url and video_hash interact when both are provided. With 0% coverage, the description must compensate more fully and falls short.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific compound action: fetch a hash-matched OpenSubtitles result and serve it via add_subtitle. It names the resource (subtitle), the source (OpenSubtitles), and the mechanism (hash matching), which distinguishes it from generic subtitle tools like list_subtitles. However, it does not reference the many sibling tools (add_subtitle, push_subtitle) it interacts with, so the differentiation is implicit rather than explicit.

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 usage context: either pass a playable video_url while Stremio desktop is running, or provide video_hash and video_size directly. This gives the agent conditions for two distinct invocation modes. It does not state when to prefer this over manually calling add_subtitle or list_subtitles, but the complementary data requirements are well articulated.

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