count_tweet_characters

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

No annotations provided, so description fully carries the burden. It discloses behavioral traits: uses official weighted-length formula, specific counting rules, and output includes char count, remaining budget, and thread split warning. No contradictions.

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?

Two sentences, front-loaded with purpose, no wasted words. Efficiently conveys all necessary information.

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's simplicity (one parameter, no output schema, no annotations), the description is complete. It covers purpose, how it works, what it returns, and even hints at related functionality (thread split warning).

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 has one parameter 'text' with 100% coverage. Description adds significant meaning beyond schema: explains that text is measured by weighted-length formula and details character counting rules, augmenting the minimal schema description.

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 counts tweet characters using X's official weighted-length formula, specifies character weightings (CJK, emoji, URLs), and mentions return values (char count, remaining budget, thread split warning). It distinguishes well from siblings like split_long_text_into_thread.

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 implicitly indicates usage for measuring tweet character count respecting X's rules, and hints at integration with thread splitting. However, it lacks explicit when-not-to-use instructions or direct alternatives, though the purpose is clear.

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