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by art.maddegen.agent
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Newest pump.fun launches

pump_launches
Read-onlyIdempotent

The newest pump.fun tokens with dev buy, early buyers/volume, curve progress, market cap and creator launch count. Returns up to 50 of the most recent launches (seconds old) with the first-N-seconds flow already aggregated, so an agent can shortlist without replaying the chain. When to use: To discover new mints; then use launch_scan for a verdict on one of them. Price: $0.002 per call (10 free/day; after that a payment-required result lists x402 options). Errors: returns isError with a message for invalid input or an upstream failure (not charged).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoHow many of the newest launches to return. Range 1-50. Default 20.
window_sNoearly-flow window after creation. Range 30-3600. Default 300.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
launchesNo
window_sNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • addedInput schema / properties / limit / description
      Added value: +"How many of the newest launches to return. Range 1-50. Default 20."
    • changedInput schema / properties / window_s / description
      Previous value: -"early-flow window after creation"New value: +"early-flow window after creation. Range 30-3600. Default 300."
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "launches": {
+      "items": {
+        "properties": {
+          "age_s": {
+            "type": [
+              "number",
+              "null"
+            ]
+          },
+          "created_at": {
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "creator": {
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "creator_launches": {
+            "type": [
+              "number",
+              "null"
+            ]
+          },
+          "curve_progress_pct": {
+            "type": [
+              "number",
+              "null"
+            ]
+          },
+          "dev_buy_sol": {},
+          "dev_sold_sol": {},
+          "early": {
+            "type": [
+              "object",
+              "null"
+            ]
+          },
+          "mayhem": {
+            "type": [
+              "boolean",
+              "null"
+            ]
+          },
+          "mcap_sol": {},
+          "mcap_usd": {},
+          "mint": {
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "name": {
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "symbol": {
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "token_program": {
+            "type": [
+              "string",
+              "null"
+            ]
+          }
+        },
+        "type": [
+          "object",
+          "null"
+        ]
+      },
+      "type": "array"
+    },
+    "window_s": {
+      "type": [
+        "number",
+        "null"
+      ]
+    }
+  },
+  "type": "object"
+}
  2. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare readOnly/idempotent/non-destructive, so the safety profile is covered. The description goes well beyond that with pricing ($0.002/call, 10 free/day, x402 options on payment-required results) and error behavior ('returns isError ... not charged') – non-obvious operational traits an agent needs.

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?

Front-loads what the tool returns, then scopes usably with labeled 'When to use', 'Price', and 'Errors' sections. Dense but every clause carries information; only minor redundancy between the prose scope and the schema's limit cap.

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 read-only discovery tool with an output schema, the description covers the important gaps: what aggregated data comes back, the cost/rate-limit model, and error semantics. An agent has everything needed to call and interpret it.

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%, so limit and window_s are already fully documented with ranges and defaults. The description echoes the 'up to 50' cap and mentions the aggregated window but adds no syntax or interpretation beyond the schema, matching the baseline-3 case.

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?

States a specific verb and resource ('The newest pump.fun tokens') plus the exact payload it returns (dev buy, early buyers/volume, curve progress, market cap, creator launch count). The 'up to 50 of the most recent launches' scope and the named sibling launch_scan clearly distinguish it from the other pump_* tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit routing: 'When to use: To discover new mints; then use launch_scan for a verdict on one of them.' It names the alternative and the condition that selects it, leaving nothing to inference.

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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