glm_continue

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

With no annotations provided, the description carries the full burden and delivers: it discloses that the child 'keeps the full context of its earlier turns,' that work is queued behind a mid-run agent, that omitting verification yields 'completed_unverified,' and that wait_seconds blocks with 0 returning immediately. These are non-obvious runtime behaviors an agent must know before calling.

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 front-loads purpose in the first sentence, follows with a dense behavior paragraph where every sentence earns its place, and closes with an Args list that maps exactly to the schema. The quoted example ('the migration you just wrote') adds value by showing the expected message style rather than padding.

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 description covers what the tool does, when to use it, and all four parameters including session continuity, queuing, verification, and blocking semantics. An output schema exists, so the description need not enumerate return values, and the single referenced status ('completed_unverified') usefully bridges to that schema.

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 0%, and the Args section fully compensates by adding meaning the schema lacks: agent_id's provenance (from glm_delegate/glm_list), verification's role as a completion-proving command with a defined omission case, and wait_seconds as a blocking control where 0 returns at once. Every parameter receives semantics far beyond its bare title.

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 lead sentence states a specific verb and resource: 'Send follow-up work to an existing subagent, in its original session.' The qualifiers 'existing' and 'original session' clearly distinguish it from the sibling glm_delegate, which creates new agents, so there is no ambiguity about what this tool operates on.

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 gives clear usage context: agent_id is sourced 'from glm_delegate or glm_list,' and the queuing note ('if the agent is mid-run, this message runs after it') tells an agent it can send follow-ups without waiting for the agent to become idle. However, it never explicitly states when not to use it or names alternatives such as glm_await for the waiting case, so it falls short of full explicit routing guidance.

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