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scrape_posts
Destructive

Reads recent posts from a public profile on Instagram, Facebook, LinkedIn, TikTok or X, and keeps them so patterns across weeks can be seen. Use it to look at a competitor before writing, or as the first step of a workflow. It costs credits per post read, so say what it will cost first.

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": {
      "platform": "<platform>",
      "target": "<target>"
    },
    "name": "scrape_posts"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoHow many posts to read, up to 100. Defaults to 10.
targetYesA handle, a profile URL, or a search term where the network allows one.
platformYesinstagram, facebook, linkedin, tiktok or x.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior3/5

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

Adds real value beyond annotations: it discloses per-post credit cost and that data is persisted ('keeps them'). However, the annotations flag destructiveHint=true and readOnlyHint=false, and the description never explains what is destructive or what existing data may be overwritten — a notable gap for a mutation-flagged tool.

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?

Three sentences, each doing distinct work: what it does, when to use it, and the cost caveat. The capability statement is front-loaded and there is no filler.

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?

Covers purpose, usage and cost well, but for an open-world, destructive-flagged scraper with no output schema, the description omits what the stored posts replace, any auth/account prerequisites, and roughly what a call returns. Adequate but leaves meaningful gaps.

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?

Schema description coverage is 100%, so all three parameters (platform, target, limit with its default and max) are already documented. The description repeats the platform list but adds no extra semantics such as target resolution rules or search-term behavior.

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?

States a specific verb (reads) and resource (recent posts) plus the exact platforms covered, and the 'keeps them so patterns across weeks can be seen' clause distinguishes it from a one-off fetch. An agent can tell it apart from siblings like list_posts or read_source.

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?

Gives two concrete usage contexts ('look at a competitor before writing' and 'first step of a workflow'), which is clear guidance. It stops short of naming alternatives such as estimate_scrape_cost or list_scrapers, so the when-to-use-this-vs-that routing is only implied.

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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