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list_opportunities

Read-only

List all opportunities for discovery, with optional filters for problem text, workflow status, and sorting by fields like idea count.

Instructions

List all opportunities. START HERE for discovery.

USE WHEN: "Show opportunities", "Discovery pipeline", "Opportunities about onboarding" Optional server-side filters: problem_contains (case-insensitive), workflow_status (exact); sort ("ideas_count desc"). Returns array of opportunities with ID, problem_statement, workflow_status, and linked idea count. FAILS WHEN: API token invalid; sort names a field outside the allowed list (the error lists them). Returns empty list if no opportunities exist.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sortNoSort as "field" or "field asc|desc" (server-side). Fields: id, problem_statement, workflow_status, location_status, description, user_id, ideas_count, bars_count
workflow_statusNoOnly opportunities in this workflow status, exact match (server-side)
problem_containsNoOnly opportunities whose problem statement contains this text (case-insensitive, server-side)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesThe ProductPlan payload (object or array) returned by the API, passed through verbatim
summaryYesHuman-readable summary of the result (e.g. "Found 3 roadmaps")

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv6.0.0
    • addedInput schema / properties
      Added value: +{
+  "problem_contains": {
+    "description": "Only opportunities whose problem statement contains this text (case-insensitive, server-side)",
+    "type": "string"
+  },
+  "sort": {
+    "description": "Sort as \"field\" or \"field asc|desc\" (server-side). Fields: id, problem_statement, workflow_status, location_status, description, user_id, ideas_count, bars_count",
+    "examples": [
+      "problem_statement asc"
+    ],
+    "pattern": "^(id|problem_statement|workflow_status|location_status|description|user_id|ideas_count|bars_count)( (asc|desc))?$",
+    "type": "string"
+  },
+  "workflow_status": {
+    "description": "Only opportunities in this workflow status, exact match (server-side)",
+    "type": "string"
+  }
+}
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "data": {
+      "description": "The ProductPlan payload (object or array) returned by the API, passed through verbatim",
+      "type": "object"
+    },
+    "summary": {
+      "description": "Human-readable summary of the result (e.g. \"Found 3 roadmaps\")",
+      "type": "string"
+    }
+  },
+  "required": [
+    "summary",
+    "data"
+  ],
+  "type": "object"
+}
  2. First observedv5.0.0

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, and the description adds value by detailing return contents (array with ID, problem_statement, workflow_status, linked idea count), empty-list behavior, and two specific failure modes (invalid token, sort field outside allowed list). This goes beyond the annotation's binary safety signal, though it doesn't mention rate limits or pagination.

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?

The description is compact and well-organized into labeled sections (USE WHEN, filters, returns, FAILS WHEN). It front-loads the core purpose and avoids redundancy, though the 'USE WHEN' examples and filter details could be trimmed slightly without losing meaning.

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?

For a read-only list tool with three optional parameters and an output schema, the description covers the essential call context: what is returned, when it fails, and how filters behave. It does not mention pagination or result limits, but these are not critical for a list endpoint of this simplicity, and the output schema fills remaining gaps.

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?

The input schema has 100% description coverage, so the schema already documents each parameter's meaning and constraints. The description merely restates the filter semantics (case-insensitive, exact match) and gives one sort example, adding marginal value. Baseline 3 applies because the schema does the heavy lifting.

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 clearly states the resource ('opportunities') and the verb ('List'), making the purpose unambiguous. It also adds a 'START HERE for discovery' hint that signals its role as an entry point, but it does not explicitly name any sibling tool (e.g., get_opportunity) to differentiate, so it misses the top score.

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 provides concrete USE WHEN examples ('Show opportunities', 'Discovery pipeline') and explains failure conditions (invalid token, invalid sort field). It does not explicitly exclude alternative tools or mention when to prefer a sibling, but the triggers are clear enough for an agent to decide.

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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