add_watched_source

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explains the core behavior (new posts auto-appear on scrape) but omits details like duplicate handling, validation errors, permission requirements, or reversibility. The description provides baseline transparency but lacks depth for a mutation-style tool.

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, well-structured sentence that front-loads the purpose and includes a meaningful behavioral outcome. Every word contributes value with no 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?

The tool is relatively simple (3 params, no nested objects, no output schema) and the description covers the essential purpose and effect. It doesn't explain what happens on duplicate adds or the return value, but the schema and sibling tool names (list_watched_sources, remove_watched_source) fill in much of the surrounding context. Overall it is adequately complete for the tool's complexity.

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?

Schema description coverage is 100%, so the input schema already fully documents each parameter with type and examples. The description restates the source types (X, RSS, YouTube) but adds no new meaning beyond the schema. Per the rubric, the baseline is 3 when schema coverage is high, and the description does not go beyond it.

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 the verb 'Watch' to indicate adding a source, and specifies the resource types (X user, RSS feed, YouTube channel). It clearly conveys the action and scope, though it doesn't explicitly use the word 'add' or contrast with sibling tools like list_watched_sources or remove_watched_source. The effect ('new posts auto-appear in Burn Flame') adds helpful context.

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 behavior description ('new posts auto-appear in Burn Flame on each scrape') implies this tool is used to set up ongoing monitoring, which gives some usage context. However, it does not explicitly state when to use this tool versus alternatives, nor does it mention exclusions or prerequisites. Guidance is implied rather than stated.

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