All release walkthroughs

LIQUILENS · PLUGIN REVIEW EVIDENCE

Source Data Research Workspace

Five public research workflows, shown with actual captured MCP requests and results.

90 seconds · edited browser recording · no audio · no model API calls for this recording.

Inspect the interactive capture viewer · Case transcript · Recording manifest · Underlying service captures

What this demonstrates

The video shows direct calls to the public MCP service and preserves returned source dates, restrictions and unavailable states. It is not a native plugin-installation recording or a new model-routing test. Negative model cases remain unexecuted in this capture.

The product skill and negative model-routing cases are review expectations, not newly executed model tests. No trading, enrollment, collection, private-record access or execution was performed. NoiseFloor examples use synthetic inputs; all other values retain their service-provided dates and restrictions.

Cases shown

  1. Funding workspace overview

    Read the Seiche research workspace and summarize coverage, source freshness, gaps and snapshot identifier.

    Interpretation boundary: Use product seiche; retain independent source clocks, snapshot identity and unavailable evidence without treating response time as observation time.

  2. Institution dataset discovery

    Discover datasets available for LiquiLens research and explain each dataset's coverage and rights.

    Interpretation boundary: Use product liquilens, preserve exact dataset IDs and rights, and avoid presenting registry presence as complete financial coverage.

  3. Bounded observation retrieval

    Discover a permitted Seiche dataset and metric, then retrieve at most twenty observations using their exact returned IDs. Preserve units, dates, citations and missing values.

    Interpretation boundary: Use product seiche for discovery, copy exact dataset and series IDs, and set observation limit 20. Stop if no permitted series is available; do not infer historical availability.

  4. Tracked institution coverage

    Search existing Indian dossiers for 'AU', return at most ten results and explain financial-evidence gaps and population overlap.

    Interpretation boundary: Use scope dossiers, q AU and limit 10. Retain source clocks and gaps; do not treat overlapping populations as a global institution census.

  5. Settlement analysis

    Read Undertow's descriptive research analysis and explain returned settlement findings, input references and limitations.

    Interpretation boundary: Use product undertow, cite returned inputs and scope, and preserve withheld or unavailable analysis without causal or execution claims.

Endpoint: https://agents.seiche.info/products/research-data/mcp

Video SHA-256: 82fe2bebbf1462cc7d3c635660d1d85058d3af2af13150214f8bb9b3189d17a3

Draft review evidence. This page is not an OpenAI approval or publication receipt.