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mcp-content-pipeline

mcp-content-pipeline

by berkayildi
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

sync_to_github

Push analysed video and X feed results as markdown files to a configured GitHub repository to persist outputs after analysis.

Instructions

Push analysed content as markdown files to a GitHub repository.

Syncs video analyses and X feed digests to a configured GitHub repo. Use after analyse_video or analyse_x_feed to persist results.

Args: analyses: List of analysis result objects from analyse_video commit_message: Git commit message (default: 'Add video analyses') x_digests: Optional list of X digest analysis objects from analyse_x_feed

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "analyses": "<analyses>"
    },
    "name": "sync_to_github"
  }
}

Input Schema

NameRequiredDescriptionDefault
analysesYes
x_digestsNo
commit_messageNoAdd video analyses

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.15.1
    • removedInput schema / properties / image_paths
      Removed value: -{
-  "anyOf": [
-    {
-      "items": {
-        "additionalProperties": true,
-        "type": "object"
-      },
-      "type": "array"
-    },
-    {
-      "type": "null"
-    }
-  ],
-  "default": null,
-  "title": "Image Paths"
-}
  2. First observedv0.14.1

TDQS

A4/5.0
Behavior3/5

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

With no annotations, the description must carry the whole behavioral burden, and it does disclose the essentials: this writes files to an external GitHub repo (a real side effect) and consumes outputs from specific upstream tools. It omits anything about auth/permissions on the target repo, what happens if files already exist (overwrite vs. new commit), failure behavior, or whether the repo is user- or server-configured beyond the word 'configured'.

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 short, front-loaded with the action and destination, and the Args block is scannable. There is mild redundancy between 'Push analysed content as markdown files' and 'Syncs video analyses and X feed digests', which repeats the same idea in different words.

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?

Return values need not be explained because an output schema exists, and the argument provenance is covered. However, for an unannotated tool with external write side effects, the description leaves out authorization requirements and overwrite/idempotency semantics, which are things an agent should know before invoking it.

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?

Schema description coverage is 0%, so the description must compensate, and the Args block documents all three parameters: analyses (sourced from analyse_video), commit_message with its default, and x_digests as optional and sourced from analyse_x_feed. It does not describe the internal shape of the analysis objects, which is the remaining gap given the schema types them only as generic objects.

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 first line names a specific verb (push) and destination resource (markdown files in a GitHub repository), and the second line clarifies exactly what content is synced (video analyses and X feed digests). This is clearly distinguishable from the analysis siblings, which produce the data rather than persist it externally.

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 line 'Use after analyse_video or analyse_x_feed to persist results' gives an explicit ordering constraint and names the two sibling tools that feed it, which is exactly the routing information an agent needs. It stops short of stating when NOT to use it (e.g., no repo configured, or read-only workflows), so it is clear context without exclusions.

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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