discipline_tokens_auto_emit

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

No annotations are provided, so the description carries the full burden. It discloses the API endpoint, that tokens are stored in the DB, and that a subsequent flow_update will pass via implicit self-approval. However, it does not mention any potential side effects or authorization requirements, slightly reducing transparency.

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 front-loaded with the core purpose and endpoint, and uses a clear structure: main action, preferred alternative, fallback scenario. It is somewhat long due to the inclusion of ticket numbers and field details, but each sentence adds value for an AI agent deciding whether to use the tool.

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 has only 2 parameters and no output schema, the description is complete. It covers the purpose, usage context, fallback rationale, and the effect on subsequent flow_update calls. No further context is necessary for correct invocation.

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% and both parameters are documented in the schema. The description adds minimal extra meaning beyond what the schema provides—it implies that targetState is the transition for which tokens are needed, but does not elaborate on the enum values or the format of flowId. 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?

The description clearly states that the tool performs 'bulk auto-emit of all discipline-tokens required for a target transition' and provides the HTTP endpoint. It distinguishes itself from sibling tools like flow_update by explicitly stating a preferred alternative (DF-435 body fields on flow_update) and positioning itself as a fallback.

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 explicit guidance on when to use this tool: as a fallback when the body-field path is not available (e.g., older backend) or when a token is missing after a 403 discipline_incomplete error. It also states when not to use it—preferring the flow_update body fields when possible.

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