chc-social

social_learn

Learns or verifies how to post on a target site via the browser using its network and URL, with optional recipe saving for reuse.

Instructions

Learn (or verify) how to post on any site via the browser.

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": {
      "network": "<network>",
      "url": "<url>"
    },
    "name": "social_learn"
  }
}

Input Schema

Name	Required	Description	Default
`url`	Yes
`save`	No
`network`	Yes
`dom_text`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.2.1Nov 10, 2026

TDQS

C2.1/5.0

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 behavioral burden. It does not disclose whether the tool opens a browser, performs a real post, writes persistent data, requires authentication, or merely returns learned instructions; 'verify' suggests possible side effects that are left unexplained.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single short sentence with no wasted text, so it is concise. However, the parenthetical and phrase 'any site' introduce ambiguity rather than useful structure, and the sentence is not sufficiently front-loaded about what the tool actually returns or does.

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

Completeness1/5

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

For a tool with four parameters, two required fields, no annotations, and no output schema, the description is far too thin. It gives no behavioral details, no parameter semantics, and no indication of return values or side effects.

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

Parameters1/5

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

Schema description coverage is 0% across four parameters. The description does not explain what url, network, save, or dom_text mean, which parameters are required together, or how save and dom_text affect behavior, leaving parameter meaning entirely undocumented.

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

Purpose3/5

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

The description states a verb and resource ('Learn (or verify) how to post on any site via the browser'), so the general purpose is recognizable. However, 'learn' is ambiguous—it could mean return instructions, generate a recipe, or perform a test post—and the definition does not distinguish this tool from siblings like social_recipes or social_post.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No when-to-use guidance is provided. The parenthetical '(or verify)' hints that verification is possible, but the description never says when to choose this over social_recipes, social_post, or other posting tools, nor does it state prerequisites.

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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