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Imf Portwatch

by io.github.pipeworx-io

Chokepoint Daily Traffic

chokepoint_daily_traffic
Read-onlyIdempotent

Daily vessel counts and aggregate capacity (deadweight tonnage) transiting a specific chokepoint. Returns time series ordered most-recent-first, with per-cargo-type breakdown (container / dry bulk / general cargo / RoRo / tanker). Use for "is Suez traffic back to normal after the Houthi attacks", "Hormuz throughput vs 30d average", or any bet predicated on a chokepoint disruption persisting. Accepts friendly names (suez / panama / hormuz / bab-el-mandeb / etc.) or PortWatch portid (chokepoint1..8).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoLookback window in days (default 30, max 365). Data is daily.
chokepointYesFriendly name (e.g. "Hormuz", "Suez Canal") or portid ("chokepoint7")

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
latestYes
portidYes
seriesYes
sourceYes
summaryYes
portnameYes
data_lag_daysNo
days_returnedYes
freshness_noteNo

Schema Changelog

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

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "description": "Daily vessel transits through a maritime chokepoint. PortWatch publishes on a lag — data_lag_days and freshness_note say how stale the newest row is.",
+  "properties": {
+    "data_lag_days": {
+      "type": [
+        "number",
+        "null"
+      ]
+    },
+    "days_returned": {
+      "type": "number"
+    },
+    "freshness_note": {
+      "type": "string"
+    },
+    "latest": {
+      "properties": {
+        "capacity_dwt": {
+          "type": [
+            "number",
+            "null"
+          ]
+        },
+        "date": {
+          "type": "string"
+        },
+        "n_container": {
+          "type": [
+            "number",
+            "null"
+          ]
+        },
+        "n_dry_bulk": {
+          "type": [
+            "number",
+            "null"
+          ]
+        },
+        "n_general_cargo": {
+          "type": [
+            "number",
+            "null"
+          ]
+        },
+        "n_roro": {
+          "type": [
+            "number",
+            "null"
+          ]
+        },
+        "n_tanker": {
+          "type": [
+            "number",
+            "null"
+          ]
+        },
+        "n_total": {
+          "type": [
+            "number",
+            "null"
+          ]
+        }
+      },
+      "type": "object"
+    },
+    "portid": {
+      "type": "string"
+    },
+    "portname": {
+      "type": "string"
+    },
+    "series": {
+      "items": {
+        "properties": {
+          "capacity_dwt": {
+            "type": [
+              "number",
+              "null"
+            ]
+          },
+          "date": {
+            "type": "string"
+          },
+          "n_container": {
+            "type": [
+              "number",
+              "null"
+            ]
+          },
+          "n_dry_bulk": {
+            "type": [
+              "number",
+              "null"
+            ]
+          },
+          "n_general_cargo": {
+            "type": [
+              "number",
+              "null"
+            ]
+          },
+          "n_roro": {
+            "type": [
+              "number",
+              "null"
+            ]
+          },
+          "n_tanker": {
+            "type": [
+              "number",
+              "null"
+            ]
+          },
+          "n_total": {
+            "type": [
+              "number",
+              "null"
+            ]
+          }
+        },
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "source": {
+      "type": "string"
+    },
+    "summary": {
+      "properties": {
+        "avg_vessels_30d": {
+          "type": [
+            "number",
+            "null"
+          ]
+        },
+        "avg_vessels_7d": {
+          "type": [
+            "number",
+            "null"
+          ]
+        },
+        "recent_vs_baseline_ratio": {
+          "type": [
+            "number",
+            "null"
+          ]
+        }
+      },
+      "type": "object"
+    }
+  },
+  "required": [
+    "source",
+    "portid",
+    "portname",
+    "days_returned",
+    "latest",
+    "summary",
+    "series"
+  ],
+  "type": "object"
+}
  2. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "chokepoint": "Hormuz",
+    "days": 30
+  },
+  {
+    "chokepoint": "Suez Canal"
+  }
+]
  3. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Beyond the readOnlyHint and idempotentHint annotations, the description adds valuable behavioral context: results are ordered most-recent-first, include per-cargo-type breakdowns, and accept both friendly names and portid formats. This significantly enhances the agent's understanding of what to expect.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, with four sentences each serving a clear purpose: what it does, output characteristics, example queries, and input format. It is slightly dense but not overly verbose, striking a good balance.

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?

Given the presence of an output schema, the description does not need to enumerate return fields. It already covers purpose, output ordering, aggregation level, input flexibility, and realistic use cases, making it complete for an agent to select and invoke the tool correctly.

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 input schema already covers both parameters with 100% description coverage. The description adds concrete examples of valid chokepoint values (suez, hormuz, chokepoint1..8), which goes beyond the schema's generic phrasing and helps the agent formulate correct inputs.

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 clearly states the tool returns daily vessel counts and deadweight tonnage for a specific chokepoint, with time series ordering and cargo-type breakdown. This distinguishes it from sibling tools like chokepoint_compare or chokepoint_status by focusing on single-chokepoint daily traffic data.

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 provides explicit example use cases (e.g., 'is Suez traffic back to normal after the Houthi attacks', 'Hormuz throughput vs 30d average'), making the intended context clear. However, it does not explicitly mention alternative tools or negative use cases, so it falls short of full exclusion guidance.

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

A4.2/5.0
Disambiguation4/5

Most tools have clear distinct purposes, but the three ask_pipeworx variants (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) are very similar, and there is some overlap between bet_research and polymarket_edges. Overall, the majority are well-differentiated.

Naming Consistency5/5

Tool names follow a consistent snake_case verb_noun pattern with only minor deviations (e.g., 'chokepoints_list' vs 'chokepoint_daily_traffic'). The naming convention is predictable and clear.

Tool Count2/5

At 37 tools, the surface is overly large for a focused server. Many tools are meta-tools that could have been consolidated, and the count exceeds the recommended range (25+), making it feel heavy and unwieldy.

Completeness5/5

The server covers maritime chokepoints comprehensively (list, status, daily, compare, disruptions), and the Pipeworx-based tools provide broad coverage across financial, drug, prediction market, and general query domains. There are no obvious gaps for the stated scope.

Resources