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NarcoScope — illicit-economy evidence atlas

Read China and regional economic research

get_connected_research
Read-only

Return source-linked China economic findings, CPEC, Balochistan, BRI and Myanmar research questions, reporting metadata, and dated national indicators. Optional hash-bound observatory summaries add economic histories, EU-reported trade and official methodology cases. SAFE quantities remain private. Country and theme context only; gaps do not establish concealment, actor relationships or causality.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes
schemaYes
sha256Yes
source_urlYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedOutput schema / properties / data / properties / observatory
      Added value: +{
      +  "additionalProperties": false,
      +  "properties": {
      +    "datasets": {
      +      "items": {
      +        "type": "object"
      +      },
      +      "maxItems": 4,
      +      "minItems": 4,
      +      "type": "array"
      +    },
      +    "findings": {
      +      "items": {
      +        "type": "object"
      +      },
      +      "maxItems": 100,
      +      "type": "array"
      +    },
      +    "generated_at": {
      +      "type": "string"
      +    },
      +    "input_sha256": {
      +      "pattern": "^[0-9a-f]{64}$",
      +      "type": "string"
      +    },
      +    "methodology_cases": {
      +      "items": {
      +        "type": "object"
      +      },
      +      "maxItems": 30,
      +      "type": "array"
      +    },
      +    "schema": {
      +      "const": "palimpsest.china-evidence-observatory-summary.v1"
      +    },
      +    "source_url": {
      +      "const": "https://www.palimpsest.info/china/evidence/"
      +    },
      +    "use_policy": {
      +      "additionalProperties": false,
      +      "properties": {
      +        "actor_inference": {
      +          "const": "prohibited"
      +        },
      +        "concealment_inference": {
      +          "const": "not_established_by_gaps_or_disagreement"
      +        },
      +        "missing_values": {
      +          "const": "unavailable_not_zero"
      +        },
      +        "private_numeric_data": {
      +          "const": "excluded"
      +        }
      +      },
      +      "required": [
      +        "concealment_inference",
      +        "actor_inference",
      +        "private_numeric_data",
      +        "missing_values"
      +      ],
      +      "type": "object"
      +    }
      +  },
      +  "required": [
      +    "schema",
      +    "generated_at",
      +    "source_url",
      +    "input_sha256",
      +    "datasets",
      +    "findings",
      +    "methodology_cases",
      +    "use_policy"
      +  ],
      +  "type": "object"
      +}
  2. Added

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already indicate readOnlyHint=true and destructiveHint=false. The description adds meaningful behavioral context: 'SAFE quantities remain private' and 'Country and theme context only; gaps do not establish concealment, actor relationships or causality.' This goes beyond the annotations by clarifying what the tool will not reveal and how to interpret missing data. It also discloses the optional hash-bound summaries.

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 substantive sentences: the first lists core outputs, the second describes optional additions, and the third states privacy and interpretative safeguards. The content is front-loaded, dense, and every clause adds value without redundancy.

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?

For a zero-parameter, read-only tool with an output schema, the description sufficiently covers what is returned, what remains private, and how to interpret gaps. It does not explain when to prefer this tool over sibling research tools, but the topic specificity and output schema carry most of the invocation burden.

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?

The tool has zero parameters with an empty schema and 100% schema description coverage, so the baseline is 4. The description mentions 'Optional hash-bound observatory summaries' without tying them to a parameter, but since the schema disallows additional properties this is not a parameter conflict; no parameter explanation is needed.

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 'Return' and names a concrete resource: source-linked China economic findings, CPEC, Balochistan, BRI and Myanmar research questions, reporting metadata, and dated national indicators. This is specific and conveys a clear read/research purpose, though it does not explicitly contrast with sibling tools such as get_palimpsest_bri_context, so some overlap ambiguity remains.

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 explicit when-to-use guidance is provided. The caveats about SAFE quantities and gaps describe interpretation limits, not selection criteria or alternatives. An agent would have to infer when this tool is appropriate based on the topic list, leaving usage to inference rather than direction.

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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