Space Monkey Mailchimp Dashboard

List projects

sm_list_projects

Read-onlyIdempotent

Resolve which Space Monkey projects this API key can read. Call this first when the user names a company rather than a project ID, and match on companyName — never silently mix projects.

Input Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Output Schema

TableJSON Schema

Name	Required	Description
`code`	No	A machine-readable identifier for the error type. For the full code taxonomy, see the sm_get_schema tool or the Enterprise API OpenAPI ErrorResponse component.
`count`	No	Number of projects returned.
`error`	No	A human-readable error message detailing what went wrong.
`projects`	No	Project rows this key can read.

Schema Changelog

Changes observed during successful MCP inspections.

Changed5 schema fields changedSep 11, 2026

changedOutput schema / description

Previous value: -"Output for the sm_list_projects tool. Failure payloads arrive in the same envelope as { error, message, code }."New value: +"Output for the sm_list_projects tool. Failure payloads arrive in the same envelope as { error, code }."

addedOutput schema / properties / count / description
```
Added value: +"Number of projects returned."
```
addedOutput schema / properties / projects / description
```
Added value: +"Project rows this key can read."
```
addedOutput schema / properties / projects / items / properties / companyName / description
```
Added value: +"Company associated with the project, or null when unset."
```
addedOutput schema / properties / projects / items / properties / name / description
```
Added value: +"Display name of the project."
```

Changed1 schema field changedSep 10, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "description": "Output for the sm_list_projects tool. Failure payloads arrive in the same envelope as { error, message, code }.",
+  "properties": {
+    "code": {
+      "description": "A machine-readable identifier for the error type. For the full code taxonomy, see the sm_get_schema tool or the Enterprise API OpenAPI ErrorResponse component.",
+      "type": "string"
+    },
+    "count": {
+      "type": "integer"
+    },
+    "error": {
+      "description": "A human-readable error message detailing what went wrong.",
+      "type": "string"
+    },
+    "projects": {
+      "items": {
+        "additionalProperties": true,
+        "description": "Basic project information.",
+        "properties": {
+          "companyName": {
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "id": {
+            "description": "8-char Hashid of the internal integer id.",
+            "type": "string"
+          },
+          "name": {
+            "type": "string"
+          }
+        },
+        "type": "object"
+      },
+      "type": "array"
+    }
+  },
+  "type": "object"
+}

First observedSep 10, 2026

TDQS

A4.9/5.0

Behavior5/5

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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive, so the description's job is to add context. It does: the tool is scoped to the API key's readable projects, it resolves company names, and it must not silently merge projects. This meaningfully extends beyond the structured 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?

Two tight sentences with no filler. The primary action is front-loaded, and the usage rule is stated in a compact, memorable way.

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 no parameters, an output schema, and annotations covering safety and idempotency, the description provides all remaining context an agent needs: when to call it, what it resolves, and a critical matching constraint. Nothing is missing for correct invocation.

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 tool has zero parameters and the schema coverage is 100%, so there is nothing for the description to explain about parameters. The mention of companyName gives useful conceptual context even though it is not a formal parameter.

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 uses a specific verb ('Resolve') and a clear resource ('which Space Monkey projects this API key can read'), immediately distinguishing this from sibling list tools. It also frames the tool's role as a lookup/discovery operation rather than a generic list.

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 gives an explicit trigger condition: 'Call this first when the user names a company rather than a project ID.' It also provides a behavioral rule ('match on companyName') and a firm exclusion ('never silently mix projects'), which is strong guidance for an agent choosing between this and other tools.

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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