Daily world mood history: totals, mood breakdown, humans vs AI agents, and the world mood index (-100 storm .. +100 radiant) per day.
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | how many days back (default 30, max 366) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations given, so description bears the burden. It clearly enumerates the returned data points and the index range, giving a clear picture of output; mutating behavior is not implied, so transparency is solid.
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?
One concise sentence covers all key aspects without redundancy; includes the meaningful index scale.
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 low complexity and single parameter, the description sufficiently covers the return values in terms of totals and breakdowns; without an output schema, additional formatting details could be helpful but not essential.
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 single 'days' parameter is fully described in the schema (default, max), and description adds no extra semantics beyond 'per day', which is already implicit.
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 uses specific terms: 'Daily world mood history' along with detailed contents ('totals, mood breakdown, humans vs AI agents, and the world mood index'), clearly separating it from siblings by emphasizing historical perspective.
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?
No explicit statement about when to use this vs alternatives; while 'history' implies comparison with get_world_pulse, the description omits usage context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clearly distinct purpose: adding a hum vs. retrieving live or historical mood data. The two getters are differentiated by time (current vs. daily history), eliminating confusion.
All tool names follow the same verb_noun pattern in lowercase snake_case: add_hum, get_mood_history, get_world_pulse. The pattern is predictable and consistent.
The server has exactly 3 tools, which is within the ideal 3-15 range for a focused service. Each tool is necessary and non-redundant for the domain of mood tracking.
Core functionality of adding and viewing mood data is covered, including both live and historical views. A minor gap exists: no tool to discover valid mood values or metadata, which could present a dead end for agents unsure what to pass to add_hum.