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URLpipe

Inspect a past request

get_request
Read-onlyIdempotent

Everything about one past request except its result: what was asked for, how long each stage took, whether it came from the store, and how the webhook delivery went.

This is the metadata; get_result returns the page itself. Reach for this one when a call did not do what you expected — it says whether the result was reused, why an analysis failed, and whether the delivery to the project's endpoint succeeded.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tokenYesThe token the original call returned.
project_idYesFrom list_projects.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
metaNoWhat the HTTP response headers would say: cache, cost, quota, result_url.
asyncNo
tokenYes
labelsNo
statusYes
creditsNo
max_ageNo
outcomeNo
successNo
operationNo
report_toNo
created_atNo
operationsNo
duration_msNo
finished_atNo
webhook_errorNo
webhook_statusNo
request_optionsNo
served_from_cacheNo
webhook_delivered_atNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "$schema": "https://json-schema.org/draft/2020-12/schema",
      +  "properties": {
      +    "async": {
      +      "type": [
      +        "boolean",
      +        "null"
      +      ]
      +    },
      +    "created_at": {
      +      "type": "string"
      +    },
      +    "credits": {
      +      "type": "integer"
      +    },
      +    "duration_ms": {
      +      "type": "integer"
      +    },
      +    "finished_at": {
      +      "type": "string"
      +    },
      +    "labels": {
      +      "additionalProperties": {
      +        "type": "string"
      +      },
      +      "type": "object"
      +    },
      +    "max_age": {
      +      "type": [
      +        "integer",
      +        "null"
      +      ]
      +    },
      +    "meta": {
      +      "description": "What the HTTP response headers would say: cache, cost, quota, result_url.",
      +      "type": "object"
      +    },
      +    "operation": {
      +      "type": [
      +        "string",
      +        "null"
      +      ]
      +    },
      +    "operations": {
      +      "items": {
      +        "properties": {
      +          "created_at": {
      +            "type": "string"
      +          },
      +          "credits": {
      +            "type": "integer"
      +          },
      +          "duration_ms": {
      +            "type": "integer"
      +          },
      +          "finished_at": {
      +            "type": "string"
      +          },
      +          "labels": {
      +            "additionalProperties": {
      +              "type": "string"
      +            },
      +            "type": "object"
      +          },
      +          "operation": {
      +            "type": [
      +              "string",
      +              "null"
      +            ]
      +          },
      +          "served_from_cache": {
      +            "type": [
      +              "boolean",
      +              "null"
      +            ]
      +          },
      +          "status": {
      +            "type": "string"
      +          },
      +          "success": {
      +            "type": [
      +              "boolean",
      +              "null"
      +            ]
      +          },
      +          "token": {
      +            "type": "string"
      +          },
      +          "url": {
      +            "type": "string"
      +          }
      +        },
      +        "required": [
      +          "token",
      +          "url",
      +          "status"
      +        ],
      +        "type": "object"
      +      },
      +      "type": "array"
      +    },
      +    "outcome": {
      +      "type": [
      +        "object",
      +        "null"
      +      ]
      +    },
      +    "report_to": {
      +      "type": [
      +        "string",
      +        "null"
      +      ]
      +    },
      +    "request_options": {
      +      "type": [
      +        "object",
      +        "null"
      +      ]
      +    },
      +    "served_from_cache": {
      +      "type": [
      +        "boolean",
      +        "null"
      +      ]
      +    },
      +    "status": {
      +      "type": "string"
      +    },
      +    "success": {
      +      "type": [
      +        "boolean",
      +        "null"
      +      ]
      +    },
      +    "token": {
      +      "type": "string"
      +    },
      +    "url": {
      +      "type": "string"
      +    },
      +    "webhook_delivered_at": {
      +      "type": [
      +        "string",
      +        "null"
      +      ]
      +    },
      +    "webhook_error": {
      +      "type": [
      +        "string",
      +        "null"
      +      ]
      +    },
      +    "webhook_status": {
      +      "type": [
      +        "string",
      +        "null"
      +      ]
      +    }
      +  },
      +  "required": [
      +    "token",
      +    "url",
      +    "status"
      +  ],
      +  "type": "object"
      +}
  2. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds useful behavioral context by enumerating what the metadata contains: stage durations, store reuse, analysis failure reasons, and webhook delivery status. It does not contradict the annotations.

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?

The description is tight and well-structured: the first sentence states scope, and the second provides routing guidance and diagnostic value. Every sentence earns its place with no filler.

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?

With a 2-parameter schema that is fully described, an output schema, and annotations covering safety and idempotency, the description gives the agent everything needed to correctly choose and use the tool. It even supplies diagnostic use cases that are not implied by the schema.

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 the schema already documents both parameters well. The description does not add significant parameter-level detail, but it doesn't need to because project_id and token are already explained ('From list_projects' and 'The token the original call returned').

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 identifies the tool as inspecting metadata about a past request, explicitly excluding the result. It differentiates itself from get_result by saying 'This is the metadata; get_result returns the page itself.'

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?

It tells the agent exactly when to use this tool: 'Reach for this one when a call did not do what you expected.' It also names the alternative (get_result) and explains the distinction, leaving no ambiguity about when to choose this over its sibling.

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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