telegram_search

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

No annotations are provided, so the description bears the full burden. It mentions query matching behavior (AND, space-separated), default values for hours, limit, and channel, but does not discuss result ordering, pagination, case sensitivity, or rate limits. This is adequate but leaves some gaps.

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 concise, front-loaded with purpose, and structured with clear sections (purpose, matching details, parameter list). Every sentence adds value, and there is no repetition or fluff.

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 4 parameters, 1 required, and the existence of an output schema, the description covers the core behavior and all parameters thoroughly. It provides enough context for an agent to invoke the tool correctly without needing additional clarification.

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?

With 0% schema description coverage, the description fully compensates by explaining each parameter: query (keywords, AND match), hours (time range, default 72), limit (max results, default 30), channel (username without @, omit for all). This adds critical meaning beyond the bare schema.

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 does full-text search of original messages by keyword/topic, and explicitly distinguishes from sibling tools by noting it can find posts without stock codes (e.g., macro/industry/theme). The verb '전문검색' and phrase '내용 축 도구' make purpose specific and differentiated.

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 explains when to use (keyword searching for content, including without stock codes) and provides matching behavior (space-separated AND match, 3+ chars for speed). It does not explicitly mention when not to use, but the context is clear enough to guide selection among siblings.

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