ecosystem_deep_review_request_batch

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 tool's behavior: it pulls active+shallow_done profiles, creates database rows, and returns DispatchIntent payloads. It also notes that the leader must spawn agents, which is a key behavioral trait. However, it does not discuss authorization or error conditions.

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 a clear one-line summary: 'Stage 1 — Queue architecture-analysis dispatches for tag-filtered candidates.' The subsequent sentences are informative but could be slightly more streamlined. Every sentence provides necessary context, earning its place.

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 complexity (batch processing, multiple steps) and the presence of an output schema, the description covers the essential flow: candidate selection, row creation, and return of dispatch intents. It also mentions the leader's role and the downstream tool call. It lacks error handling details but is generally complete for an agent to use.

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. The description adds meaning by explaining the 'AND semantics' for the tags parameter and the overall filtering logic ('Pulls active+shallow_done profiles whose tag set covers tags'). It also clarifies the research_goal parameter's purpose ('injected into each sub-agent prompt'). This adds value beyond the 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's function: 'Queue architecture-analysis dispatches for tag-filtered candidates.' It uses specific verbs like 'pulls,' 'creates,' and 'returns,' and distinguishes itself from sibling tools like ecosystem_deep_review_request by indicating it operates on a batch of candidates.

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 provides context on when to use the tool (Stage 1) and includes instructions that the leader is responsible for spawning agents via the Agent tool, implying a multi-step workflow. It does not explicitly state when not to use it or suggest alternatives, but the sibling list provides context for differentiation.

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