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trimtab-ais

by io.github.mrsingh86

Pre-registered event studies

event_studies
Read-only

Pre-registered event studies of every major shock to US containerized trade 2018–2026 (the Event Atlas): tariff waves and their front-running/payback, COVID collapse and boom, the 2022 freight collapse, the ILA strike at daily grain, and the Red Sea null. Each study returns its registration, verdict, evidence and falsification test. Run against US Census port records and customs duty receipts. No API key required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugNoOptional study slug for full detail (e.g. hidden-queue, red-sea-null, india-tariff-suppression). Omit to list all studies with verdicts.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already cover read-only and non-destructive behavior. The description adds valuable behavioral context: the studies are pre-registered, responses include specific components (registration, verdict, evidence, falsification test), and no authentication is needed. This goes beyond what annotations provide.

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 dense sentences cover scope, examples, return contents, data sources, and authentication. No filler or repetition; the most distinguishing information (pre-registered, specific shocks) is front-loaded.

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

Completeness5/5

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

For a tool with one optional parameter, no output schema, and read-only annotations, the description fully equips an agent: what it is, what it returns, what data it runs on, and access requirements. Nothing essential is missing.

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%, and the schema already explains the optional slug parameter with examples and the omission behavior. The tool description itself does not add parameter-level detail, so the baseline of 3 applies.

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?

The description names a specific resource ('Event Atlas' pre-registered event studies) and explains what each study returns (registration, verdict, evidence, falsification test). It is clearly distinct from sibling trade tools by its focus on curated shocks and pre-registration methodology.

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?

The description clearly implies when to use it — when the agent needs pre-registered event studies of major shocks to US containerized trade. It also specifies the data sources and notes no API key is required. It does not explicitly name alternatives or exclusions, but the context is sufficiently clear for selection.

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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TDQS

A3.9/5.0
Disambiguation2/5

Several tools overlap significantly in the tariff/trade domain: tariff_story explicitly replaces hs_search, tariff_lookup, and tariff_burden, and trade_query also returns duty data. This creates ambiguity about which tool to invoke for a given tariff question, though non-tariff tools (compare, event_studies, month_in_review) are clearly distinct.

Naming Consistency2/5

Tool names follow mixed conventions: some are verb-first (compare, query_series, tariff_lookup), others are noun-first (commodity_profile, tariff_burden, event_studies), and there's no consistent prefix or verb pattern. While readable, the lack of a unified naming scheme makes the set feel less coherent.

Tool Count4/5

With 13 tools, the set is within a reasonable range for a trade data service and covers most query needs. It's slightly larger than necessary given the overlapping tariff tools, but not excessive.

Completeness4/5

The surface covers tariff lookup, actual duties paid, trade volumes, comparisons, profiles, event studies, and rulings search, which is comprehensive for a read-only trade data resource. Minor gaps exist (e.g., no tool for gateway-specific tariff burden, and the meta-tool ledger_meta hides a set of archived tools), but core workflows are well supported.

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