# Gdelt Mentions Fetch

> Retrieve bounded GDELT 2.0 Global Mentions rows through the Tiangong CLI from the latest snapshot or an exact UTC range. Use for mention-level provenance, confidence, and source linkage around coded events; do not use for article bodies, unique-article counts, event verification, polling, bulk archival mirroring, or causal claims.

- Skill: `tiangong-ai/gdelt-mentions-fetch` (Agent Skill, multi-file: 3 files)
- Install (CLI): `npx skillmds add tiangong-ai/gdelt-mentions-fetch`
- Raw SKILL.md: https://api.skillmd.com/api/skills/tiangong-ai/gdelt-mentions-fetch/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: tiangong-ai (https://skillmd.com/u/tiangong-ai)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/tiangong-ai/gdelt-mentions-fetch

---


# GDELT Mentions Fetch

Use the CLI-owned `gdelt.mentions` capability. This Skill supplies intent
routing and result-use boundaries only; the CLI owns source discovery,
input/output schemas, HTTP and archive handling, limits, validation, and
receipts.

## Before running

1. Read `references/tiangong-data-requirement.json`.
2. Use the caller- or workspace-resolved stable CLI. The requirement declares
   compatible capability and operation contract majors; it does not select a
   package build.
3. Run `data describe` with that same CLI. Continue only when the capability
   ID and required contract majors match, and copy the exact current
   capability/operation versions from that response into the run request.

```bash
tiangong-ai data describe gdelt.mentions --json
```

Use the returned Discovery Metadata to confirm current source coverage,
freshness, restrictions, `provides`, and `doesNotProvide`. Do not substitute
facts remembered from an older Skill revision.

## Prepare the request

Build a `tiangong.data.run-request.v1` envelope. Replace the two version
placeholders with the exact versions from the same `data describe` response. This example selects a
bounded range of source snapshots:

```json
{
  "schemaVersion": "tiangong.data.run-request.v1",
  "capabilityId": "gdelt.mentions",
  "capabilityVersion": "<describe.manifest.capabilityVersion>",
  "operationId": "fetch",
  "operationVersion": "<describe.manifest.operations[0].operationVersion>",
  "input": {
    "mode": "range",
    "startDateTime": "2026-03-01T12:00:00Z",
    "endDateTime": "2026-03-01T12:45:00Z",
    "maxFiles": 4
  }
}
```

Use the operation input schema returned by the same `data describe` response when choosing
`latest` or `range`. Range bounds do not need to align to a 15-minute boundary:
selection starts with the first published snapshot at or after the inclusive
lower bound and stops at the inclusive upper bound. `maxFiles` selects the
earliest bounded snapshots from a larger window and must be treated as
truncation, not complete window coverage. Do not round timestamps, widen a
range, or increase a safety limit without the caller's approval.

## Run

```bash
tiangong-ai data run gdelt.mentions fetch \
  --input /absolute/path/to/request.json --json
```

The command emits a `tiangong.data.run-result.v1` envelope. Preserve its
`contract`, `warnings`, `errors`, and `receipt` with `data` when handing the
result to another workflow.

## Result boundaries

- Treat each row as a machine-coded mention of an event record, not a verified
  event, independent endorsement, unique article, or causal evidence.
- Confidence, tone, mention type, and character offsets are provider-derived
  metadata. Do not reinterpret them as factual certainty or human judgment.
- A source URL is lineage metadata, not an article body. Repeated mentions or
  URLs require explicit downstream counting and deduplication rules.
- The capability returns normalized in-memory rows and execution metadata. It
  does not create a durable ZIP mirror, expose the master file list, or perform
  polling and incremental state management.
- Preserve each file's SHA-256, ZIP/CRC validation metadata, row counts, and
  capped validation issues. Invalid UTF-8 or non-16-column rows are omitted
  locally while valid rows from the same snapshot remain usable.
- Surface `partial`, truncation warnings, archive-validation failures, and empty
  results. Never reinterpret them as complete absence of mentions.
- Use the dedicated Events or GKG Skill for their row types; this Skill must not
  invoke or combine other feeds automatically.
- Cross-source comparison, persistence, scheduling, and research evidence
  admission belong to the caller or Auto Research.

## Reference

- `references/tiangong-data-requirement.json`: stable capability requirement; it is not a package lock.