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

With no annotations, the description carries the burden and it discloses key behavior: the operation is queued (non-blocking), returns a child jobId, and requires verification. It also tells the agent the next step (poll status). It stops short of describing error/failure behavior, but the core behavioral contract is transparent.

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 the action and target, with the second sentence covering the return and polling behavior. No filler or repetition.

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?

For a two-parameter tool with no output schema, the description supplies the preconditions, the return value, and the follow-up polling action. It is slightly thin on failure/error conditions, but complete enough for an agent to invoke and process the result.

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 coverage is 100%, so both jobId and prompt are already documented. The description restates the recency constraint for jobId ('latest completed round') and frames prompt as a follow-up task, reinforcing but not adding meaning beyond the schema. Baseline 3 is appropriate.

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?

States a precise action (queue a follow-up) and a specific resource (verified Quick Chat thread), clearly differentiated from siblings by emphasizing the same thread and returning a child jobId. It also names the polling sibling, so an agent can distinguish from gpt56_pro_start and gpt56_pro_status.

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?

Gives explicit preconditions: the target must be the latest completed round and must have a captured chat title, and directs the agent to poll gpt56_pro_status. It does not explicitly name gpt56_pro_start as the alternative for new threads, but the phrase 'follow-up in the verified same Quick Chat thread' strongly implies it.

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

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

With no annotations, the description carries the burden and discloses key behavior: immediate return with jobId, daemon serialization, UI verification, and external lifecycle state. It does not mention failure modes or idempotency, but the async nature and polling requirement are clearly conveyed.

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?

Three sentences each serve a distinct purpose: stating the action, describing the return behavior, and explaining daemon internals and next step. The key information is front-loaded, and there is no filler or repetition.

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?

For a one-parameter async queue tool with no output schema, the description covers what to send, what is returned (jobId), and what to do next (poll status). It does not explicitly say how to use the jobId with siblings, but that is a minor inferable gap.

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 already documents the single 'prompt' parameter with a full description (100% coverage), so the baseline is 3. The tool description adds no new parameter-specific detail beyond the schema's own description, merely restating that the prompt is the task.

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?

States a specific verb 'Queue' and a specific resource 'GPT-5.6 sub-agent job', making the tool's role clear. The phrase 'for this MCP workspace' scopes it further, and the sibling tools (status, followup) are implied to have different purposes. The description distinguishes this as the start action.

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?

Provides clear context that this queues a job and returns immediately, and instructs to poll gpt56_pro_status afterward. However, it does not explicitly compare to the followup sibling or state when not to use this tool, so usage is more implied than fully specified.

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

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 signals this is a read operation (non-mutating, safe to call). However, terms like 'authoritative daemon state' and 'cooperative control-file report' are unexplained jargon that obscure the actual behavior and return semantics. The description gives hints (read-only, latest/validated data) but doesn't disclose what an agent will actually receive or whether repeated calls are safe.

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?

A single sentence with no filler words, front-loading the key verb 'Read' and specifying the resource. The structure is efficient — a busy agent can extract the action quickly. Points are deducted only because the dense, jargony phrasing ('authoritative daemon state', 'validated cooperative control-file report') achieves brevity at the expense of immediate clarity.

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?

For a status-checking tool with no output schema and no annotations, the description carries significant responsibility, and it's mostly adequate: it conveys read-only semantics and a job-scoped scope. However, it doesn't clarify what an agent will do with the output (e.g., does it return a job state like pending/running/completed?) or how 'daemon state' differs from the 'control-file report.' The existence of siblings suggests a workflow (start → status → followup), but the description doesn't articulate where the boundaries lie.

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 baseline is 3 with no additional parameter info needed. The description's phrase 'for a job in this MCP workspace' loosely references the job context, but the schema already documents that jobId comes from gpt56_pro_start or gpt56_pro_followup. The description adds no meaning beyond what the schema provides, which is acceptable given full coverage.

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 a specific verb ('Read') and identifies a concrete resource ('authoritative daemon state and the latest validated cooperative control-file report') scoped to a job in the MCP workspace. It clearly distinguishes from siblings: start and followup are different operations, so an agent would not confuse this with them. The phrase 'in this MCP workspace' adds a scoping qualifier that reduces over-flagging as a general system status tool.

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: check status of a job in the MCP workspace, presumably after gpt56_pro_start or gpt56_pro_followup. However, there's no explicit guidance on when to prefer this tool over siblings, when polling is appropriate, or what conditions would call for gpt56_pro_followup instead. The context is implied by the workflow rather than stated.

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