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Chinng AI-Agent Portal

portal_get

Fetch a full article by id.

The body/summary returned is gated by license_note:

  • full (default): body included

  • summary-only: no body, summary (summary/summary_en) present

  • link-only: link and metadata only, no summary or body

Args: id: article id (e.g. "news-20260702-4c769f") include_body: false to return metadata only, omitting the body (even when license is full)

Returns: The article's full metadata + body (body_policy states which policy was applied). Returns {error: "not_found", id} if the article does not exist.

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": {
      "id": "<id>"
    },
    "name": "portal_get"
  }
}

Input Schema

NameRequiredDescriptionDefault
idYes
include_bodyNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations supplied, the description carries the full burden and does well: it enumerates the three license_note policies and exactly what each returns, notes that include_body=false overrides even a full license, states body_policy is reported back, and documents the {error: "not_found"} case. It never states this is a read-only operation or discusses permissions, which is the remaining gap.

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?

Front-loaded one-line purpose followed by clearly labeled gating rules, Args, and Returns. Every sentence carries information an agent needs to invoke the tool correctly; nothing is padding.

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

Completeness4/5

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

An output schema exists, so the Returns section is partly redundant, yet it usefully flags the error shape and body_policy field. Combined with full parameter explanation and gating behavior, an agent has enough to call this correctly; only auth/permission context is absent.

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 it does: it gives an id format example ('news-20260702-4c769f') and explains include_body's exact effect including its interaction with license gating. It does not restate the boolean default, but the behavior is unambiguous.

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 opens with a specific verb+resource ('Fetch a full article by id'), which cleanly separates it from the listing/search siblings like portal_search and portal_list. It stops short of naming an alternative explicitly, but 'by id' versus search-style siblings is unambiguous.

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

Usage Guidelines3/5

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

Usage context is clear from the Args section (call it when you have an article id) and from the license_note gating rules that govern what comes back. However, there is no explicit when-to-use/when-not guidance relative to portal_search or portal_get_agent_surface, so the agent must infer selection from name alone.

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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