velog_draft_post

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that the draft is saved to session memory and returns a draft_id for review, which is useful. However, it lacks critical details: it doesn't specify if this is a read-only or mutation operation (implied mutation but not explicit), doesn't mention authentication requirements, rate limits, or what happens to the draft after saving (e.g., expiration, storage duration). For a tool with no annotations, this leaves significant gaps in understanding its behavior.

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 and front-loaded: it states the core action in the first sentence and the key outcome in the second. Every sentence earns its place by explaining what the tool does and why, with no redundant or vague language. It's appropriately sized for the tool's complexity, making it easy to understand quickly.

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 moderate complexity (5 parameters, no output schema, no annotations), the description provides a basic but incomplete picture. It covers the purpose and high-level usage context but lacks behavioral details like mutation effects, authentication, or error handling. Without annotations or an output schema, the description should do more to explain the return value (draft_id usage) and operational constraints. It's minimally viable but has clear gaps for a tool that modifies data.

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 schema description coverage is 100%, with all parameters well-documented in the input schema (e.g., title, body, tags, is_private, short_description). The description doesn't add any parameter-specific information beyond what's in the schema, such as format details or usage examples. Given the high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't need to since the schema handles parameter semantics adequately.

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's purpose: 'Velog 포스트 초안을 세션 메모리에 저장합니다' (saves a Velog post draft to session memory). It specifies the action (save to session memory) and resource (Velog post draft), distinguishing it from siblings like velog_publish_post (which publishes) or velog_update_post (which modifies existing posts). However, it doesn't explicitly differentiate from velog_update_post in terms of draft vs. published post editing, which could be clearer.

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 implies usage context: '발행 전 사용자가 검토할 수 있도록' (so users can review before publishing), suggesting this tool is for creating drafts prior to publication. However, it doesn't explicitly state when to use this vs. alternatives like velog_publish_post (direct publishing) or velog_update_post (editing existing posts), nor does it mention prerequisites or exclusions. The guidance is present but not comprehensive.

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