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prompteye-mcp

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TypeScript
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Read what the project knows about the brand

get_knowledge_base
Read-only

The description of the brand the project measures against — what the company sells and to whom. Everything PromptEye writes for the project reads this first, so it is worth knowing what a brand is being judged against before trusting a…

Instructions

The description of the brand the project measures against — what the company sells and to whom. Everything PromptEye writes for the project reads this first, so it is worth knowing what a brand is being judged against before trusting a prompt or a competitor.

Input Schema

NameRequiredDescriptionDefault
projectIdYesThe project to work on — its id from list_projects. Required on every call, so that parallel conversations never read or write each other's project.

Output Schema

NameRequiredDescriptionDefault
textYesThe whole profile as stored, one `Label: value` block per field. null = not described yet.
profileNoOne field per question about the brand; null where nothing is written yet.
updatedAtYesWhen the profile was last written, ISO 8601 in UTC. null = no profile yet.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv1.0.28
    • addedInput schema / additionalProperties
      Added value: +false
    • addedInput schema / properties / projectId
      Added value: +{
+  "description": "The project to work on — its id from list_projects. Required on every call, so that parallel conversations never read or write each other's project.",
+  "minLength": 1,
+  "type": "string"
+}
    • addedInput schema / required
      Added value: +[
+  "projectId"
+]
  2. Changed1 schema field changedv1.0.22
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "$schema": "https://json-schema.org/draft/2020-12/schema",
+  "additionalProperties": false,
+  "properties": {
+    "profile": {
+      "additionalProperties": false,
+      "description": "One field per question about the brand; null where nothing is written yet.",
+      "properties": {
+        "description": {
+          "type": [
+            "string",
+            "null"
+          ]
+        },
+        "icp": {
+          "type": [
+            "string",
+            "null"
+          ]
+        },
+        "industry": {
+          "type": [
+            "string",
+            "null"
+          ]
+        },
+        "operatingArea": {
+          "type": [
+            "string",
+            "null"
+          ]
+        },
+        "productCategory": {
+          "type": [
+            "string",
+            "null"
+          ]
+        },
+        "targetAudience": {
+          "type": [
+            "string",
+            "null"
+          ]
+        }
+      },
+      "required": [
+        "industry",
+        "productCategory",
+        "targetAudience",
+        "icp",
+        "operatingArea",
+        "description"
+      ],
+      "type": "object"
+    },
+    "text": {
+      "description": "The whole profile as stored, one `Label: value` block per field. null = not described yet.",
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "updatedAt": {
+      "description": "When the profile was last written, ISO 8601 in UTC. null = no profile yet.",
+      "type": [
+        "string",
+        "null"
+      ]
+    }
+  },
+  "required": [
+    "text",
+    "updatedAt"
+  ],
+  "type": "object"
+}
  3. First observedv1.0.5

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and openWorldHint, so the description need only add context beyond that. It contributes a meaningful behavioral fact — that this knowledge base is the first input to all generated content — which tells the agent why the data matters, though it does not discuss error behavior or freshness.

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?

Two sentences, front-loaded with what the resource is and followed by why it matters. The second sentence is slightly conversational but earns its place by motivating correct usage; there is no filler or repetition.

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

Completeness4/5

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

With an output schema and rich parameter schema already present, the description only needs to explain what the resource is and when to consult it. It does both adequately; an explicit pointer away from update_knowledge_base would make it fully complete.

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 fully explains projectId (its source from list_projects and the isolation rationale). The description adds no parameter-specific meaning, which is acceptable given the schema already carries the load; this is the baseline case.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description specifically identifies the resource as the brand description the project measures against — what the company sells and to whom. This makes the content clear, though it does not explicitly contrast with the sibling update_knowledge_base beyond the implicit read-vs-write distinction in the title.

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?

It gives a clear usage context: everything PromptEye writes reads this first, so an agent should read it before trusting a prompt or competitor. It stops short of naming explicit alternatives or exclusion conditions, but the when-to-use signal is strong.

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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