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

With no annotations provided, the description must fully disclose behavior. It reveals the tool reads external sources and writes to a queue ('queue anything...'), indicating a write side effect. However, it does not disclose whether the queue is persisted, if there are rate limits or authentication needs for the scanned sources, what the 'daily mention threshold' is, or if the tool modifies any existing data. The mention of 'not already solved by an existing tool' adds useful context, but overall transparency is partial.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that front-loads the mode name and primary action, then lists sources and the follow-up action. It is concise and avoids repetition. Some structure (e.g., separating scanning and queuing) is present, though adding line breaks could improve readability. The sentence earns its place but could be slightly tighter.

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

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

Given the tool has zero parameters and an output schema (not shown but indicated), the description does not need to cover return values. However, it omits important contextual details such as when to run the tool (e.g., daily schedule, trigger conditions), how the threshold is configured, and how the results relate to sibling tools like 'list_backlog' or 'develop_tools'. The description is adequate for a simple zero-parameter tool but lacks completeness for holistic understanding.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

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% (since none exist). According to guidelines, zero parameters baseline is 4. The description adds no parameter information (as none are needed), so the score matches the baseline.

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

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

The description clearly states the tool scans GitHub Issues, targeted Reddit subs, and the public MCP registry for recurring pain points not already solved by an existing tool, then queues them past a threshold. It uses a specific verb ('scan', 'queue') and resource ('pain points'), and distinguishes itself from sibling tools like 'codebase-learning-friction' or 'check_tool_health' by focusing on external source research rather than internal friction or health checks.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies the tool is for discovering new pain points from external sources, but it does not explicitly state when to use it versus alternatives like 'list_backlog' (which likely shows existing pain points) or 'deployment-process-friction' (which targets specific domains). No exclusions, prerequisites, or contextual cues are provided, leaving the agent to infer appropriate usage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.