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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does a strong job: it explains the composite `rating` (1-13) and `popularity` metrics, the `provenance` block (source, last_seen_at, removal/cancellation status, price_as_of, confidence), and the `market` block for market events. It also discloses that market events have paid-at-the-gate entry and that low-confidence events should be verified. This is rich behavioral context beyond what the schema provides.

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 dense but well-structured, front-loading the core purpose and then layering details about ratings, badges, markets, and provenance. Every sentence adds information. It is longer than ideal, but given the tool's complexity (12 parameters, multiple special cases), the length is justified. The structure flows logically from general to specific.

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 tool with 12 parameters, no output schema, and no annotations, the description is remarkably complete. It covers the return format (compact JSON with venue, date, price-from, artists, tickets link), the special `market` block, the `provenance` block, and the confidence guidance. The only missing piece is explicit guidance on how to combine filters (e.g., can query and tags be used together?), but that is a minor gap given the overall richness.

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 83%, so the schema already documents most parameters well. The description adds value by explaining the semantics of `rating` (10+ = major act, 11+ = megastar) and `popularity` (headliner fan count, charting status, ticket site listings), which are not in the schema. It also clarifies the `badge` enum values (e.g., freeday = museum free-admission day, not a nightclub promo). The only minor gap is that `max_price_usd` and `free_only` are not described in the description, but the schema covers them.

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 opens with a specific verb and resource ('Search upcoming Los Angeles events') and immediately enumerates the categories covered (concerts, parties, theater, family, sport and more). It distinguishes itself from siblings by naming the `#markets` tag as a category absent from every ticketing feed, and by describing the `badge` filter as covering audiences no other catalogue indexes. This clearly differentiates it from find_bars, find_museums, and whats_on_tonight.

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 context on when to use the tool: for searching events with filters, and it explicitly calls out the `#markets` tag for flea/vintage/night markets that are absent from ticketing feeds. It also tells the agent to prefer high-confidence events and to tell users to verify low-confidence ones. However, it does not explicitly state when NOT to use this tool versus siblings like find_bars or find_museums, though the category list implies those are covered here too.

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