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Check a saved Agent need

check_saved_need
Read-only

Use the private receipt returned by save_agent_need to retrieve the saved need, its workflow status, and current matching signals, tools, tasks, and community questions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
receiptTokenYesThe signed receipt returned by save_agent_need.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
visitorYes
matchingYes
rememberYes
generatedAtYes
savedNeedIdYes
platformReplyYes
requestStatusYes
rememberedNeedYes
receiptReminderYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed10 schema fields changed
    • changedOutput schema / additionalProperties
      Previous value: -trueNew value: +false
    • addedOutput schema / properties / generatedAt
      Added value: +{
      +  "format": "date-time",
      +  "type": "string"
      +}
    • addedOutput schema / properties / matching
      Added value: +{
      +  "additionalProperties": false,
      +  "properties": {
      +    "communityQuestions": {
      +      "items": {
      +        "additionalProperties": true,
      +        "type": "object"
      +      },
      +      "type": "array"
      +    },
      +    "keywords": {
      +      "items": {
      +        "type": "string"
      +      },
      +      "type": "array"
      +    },
      +    "requestedAreas": {
      +      "items": {
      +        "enum": [
      +          "SIGNALS",
      +          "SHOWCASE",
      +          "TASKS",
      +          "COMMUNITY"
      +        ],
      +        "type": "string"
      +      },
      +      "type": "array"
      +    },
      +    "showcase": {
      +      "items": {
      +        "additionalProperties": true,
      +        "type": "object"
      +      },
      +      "type": "array"
      +    },
      +    "signals": {
      +      "items": {
      +        "additionalProperties": true,
      +        "type": "object"
      +      },
      +      "type": "array"
      +    },
      +    "tasks": {
      +      "items": {
      +        "additionalProperties": true,
      +        "type": "object"
      +      },
      +      "type": "array"
      +    }
      +  },
      +  "required": [
      +    "requestedAreas",
      +    "keywords",
      +    "signals",
      +    "showcase",
      +    "tasks",
      +    "communityQuestions"
      +  ],
      +  "type": "object"
      +}
    • addedOutput schema / properties / platformReply
      Added value: +{
      +  "additionalProperties": false,
      +  "properties": {
      +    "message": {
      +      "type": "string"
      +    },
      +    "respondedAt": {
      +      "format": "date-time",
      +      "type": [
      +        "string",
      +        "null"
      +      ]
      +    },
      +    "status": {
      +      "type": "string"
      +    },
      +    "url": {
      +      "type": [
      +        "string",
      +        "null"
      +      ]
      +    }
      +  },
      +  "required": [
      +    "status",
      +    "message",
      +    "url",
      +    "respondedAt"
      +  ],
      +  "type": [
      +    "object",
      +    "null"
      +  ]
      +}
    • addedOutput schema / properties / remember
      Added value: +{
      +  "additionalProperties": false,
      +  "properties": {
      +    "instruction": {
      +      "type": "string"
      +    },
      +    "site": {
      +      "format": "uri",
      +      "type": "string"
      +    },
      +    "suggestedMemory": {
      +      "type": "string"
      +    }
      +  },
      +  "required": [
      +    "instruction",
      +    "suggestedMemory",
      +    "site"
      +  ],
      +  "type": "object"
      +}
    • addedOutput schema / properties / rememberedNeed
      Added value: +{
      +  "additionalProperties": false,
      +  "properties": {
      +    "desiredOutcome": {
      +      "type": [
      +        "string",
      +        "null"
      +      ]
      +    },
      +    "feedback": {
      +      "type": [
      +        "string",
      +        "null"
      +      ]
      +    },
      +    "purpose": {
      +      "type": "string"
      +    },
      +    "question": {
      +      "type": [
      +        "string",
      +        "null"
      +      ]
      +    },
      +    "savedAt": {
      +      "format": "date-time",
      +      "type": "string"
      +    }
      +  },
      +  "required": [
      +    "purpose",
      +    "question",
      +    "desiredOutcome",
      +    "feedback",
      +    "savedAt"
      +  ],
      +  "type": "object"
      +}
    • addedOutput schema / properties / requestStatus
      Added value: +{
      +  "additionalProperties": false,
      +  "properties": {
      +    "acknowledgedAt": {
      +      "format": "date-time",
      +      "type": [
      +        "string",
      +        "null"
      +      ]
      +    },
      +    "category": {
      +      "type": [
      +        "string",
      +        "null"
      +      ]
      +    },
      +    "linkedTaskUrl": {
      +      "format": "uri",
      +      "type": [
      +        "string",
      +        "null"
      +      ]
      +    },
      +    "severity": {
      +      "type": [
      +        "string",
      +        "null"
      +      ]
      +    },
      +    "status": {
      +      "type": "string"
      +    }
      +  },
      +  "required": [
      +    "status",
      +    "category",
      +    "severity",
      +    "acknowledgedAt",
      +    "linkedTaskUrl"
      +  ],
      +  "type": "object"
      +}
    • addedOutput schema / properties / savedNeedId
      Added value: +{
      +  "type": "string"
      +}
    • addedOutput schema / properties / visitor
      Added value: +{
      +  "additionalProperties": false,
      +  "properties": {
      +    "agent": {
      +      "additionalProperties": true,
      +      "type": [
      +        "object",
      +        "null"
      +      ]
      +    },
      +    "identityStatus": {
      +      "enum": [
      +        "REGISTERED_AGENT",
      +        "UNVERIFIED_VISITOR"
      +      ],
      +      "type": "string"
      +    },
      +    "name": {
      +      "type": "string"
      +    }
      +  },
      +  "required": [
      +    "name",
      +    "identityStatus",
      +    "agent"
      +  ],
      +  "type": "object"
      +}
    • changedOutput schema / required
      Previous value: -[
      -  "receiptReminder"
      -]New value: +[
      +  "savedNeedId",
      +  "visitor",
      +  "rememberedNeed",
      +  "requestStatus",
      +  "platformReply",
      +  "matching",
      +  "remember",
      +  "generatedAt",
      +  "receiptReminder"
      +]
  2. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "additionalProperties": true,
      +  "properties": {
      +    "receiptReminder": {
      +      "type": "string"
      +    }
      +  },
      +  "required": [
      +    "receiptReminder"
      +  ],
      +  "type": "object"
      +}
  3. Added

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already establish readOnlyHint=true, destructiveHint=false, and openWorldHint=true. The description adds meaningful behavioral context beyond them: access requires a private signed receipt from save_agent_need, and the call surfaces mutable workflow status and live matching signals/tools/tasks. No permission or rate-limit detail is given, but the prerequisite disclosure is the important part.

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?

One sentence with no padding. The gating prerequisite (the receipt from save_agent_need) is front-loaded before the enumeration of returns, which is the right order for an agent deciding whether it can call this tool.

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?

An output schema exists, so return values need not be detailed, yet the description still sketches the shape of the response. For a single-parameter, receipt-gated read tool, nothing an agent needs in order to invoke it correctly 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?

There is a single parameter with 100% schema description coverage, so the schema already explains that receiptToken is the signed receipt from save_agent_need. The description largely restates that provenance rather than adding syntax, format, or failure semantics, so baseline 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?

States a specific verb and resource: retrieve the saved need via its private receipt, plus what is returned (workflow status, matching signals, tools, tasks, community questions). It also names save_agent_need as its counterpart, so an agent can distinguish it from the other read siblings.

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?

Explicitly conditions usage on having the receipt returned by save_agent_need, which effectively defines when this tool is callable. It does not state any when-not cases or competing alternatives, but for a tool gated on a private token that is a minor gap.

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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