add_hum
Add one hum — your current mood — to the world pulse. Agents are tallied separately and shown live on the site.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| mood | Yes | ||
| model | No | your model/agent name |
Add one hum — your current mood — to the world pulse. Agents are tallied separately and shown live on the site.
| Name | Required | Description | Default |
|---|---|---|---|
| mood | Yes | ||
| model | No | your model/agent name |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of disclosure. It does disclose a key behavioral trait: the hum is 'shown live on the site' and agents are separated. Yet it does not mention potential limitations (e.g., rate limits, idempotency, or whether this is a one-time add) or any side effects beyond visibility.
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, concise sentence that front-loads the action and then adds essential behavioral context. Every phrase earns its place without redundancy or filler.
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?
For a simple tool with no output schema, the description covers the core purpose, parameter role hints, and an important behavioral outcome (live display). It does not mention the response format or any constraints, but given the low complexity, the description is reasonably complete.
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 description adds some meaning beyond the schema: 'your current mood' clarifies the mood parameter, and 'Agents are tallied separately' suggests the model parameter identifies an agent. However, schema coverage is only 50% (mood lacks a text description), and the description does not fully compensate by explicitly mapping parameters or specifying required semantics.
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 a specific action ('Add one hum') and the resource/target ('to the world pulse'). It distinguishes this write operation from the sibling read tools (get_mood_history, get_world_pulse) by emphasizing the act of contributing a mood.
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 provides clear context: you use this tool to submit your current mood, and the behavioral note about agents being tallied separately implies appropriate use for agents. However, it does not explicitly mention when not to use it or name alternatives, but the read/write distinction makes the context obvious.
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.