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

Annotations only declare readOnlyHint=true, so the description must carry the behavioral load, and it does add real context: default 20 rows with a hard cap of 50, top_n defaults to 3 with cap 5, and the important disclosure that `window` scopes only the news lens while price history is unaffected. It doesn't spell out the shape of the returned pulse (headline counts, price/market fields) and there is no output schema to fall back on, which keeps it from a 5.

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 short sentences, with the strongest claim ("ONE ... across every subject type") front-loaded and the replacement statement last. The middle sentence, "Pick `kind`, put the subject in `target`," largely duplicates what the fully-covered schema already says, so it isn't perfectly waste-free, but overall the text is tight.

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 seven-parameter, six-mode tool without an output schema, the description establishes scope, the consolidation story, and the key cross-parameter constraint (window affects news only). The remaining gap is what a "market pulse" actually returns — news plus market data is implied but not described — which an agent would want given no output schema exists.

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% and the parameter descriptions are themselves detailed, so the schema already does the heavy lifting. The prose adds only marginal semantics beyond it — the kind/target pairing rule and the "one context per call, shared by all tickers" note mostly restate the schema. Baseline 3 is appropriate when the schema is this complete.

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?

"ONE market-pulse read across every subject type — a news + market lens" states a specific verb (read), a specific resource (market pulse / news + market lens), and enumerates the six subject types it spans. The note that it "Replaces the per-type asset/theme/commodity/bond/macro/portfolio pulse tools" lets an agent distinguish it from siblings like theme_summary, news_feed, or financials without opening schemas.

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 a clear routing rule ("Pick `kind`, put the subject in `target`") and frames the tool as the consolidated replacement for six narrower pulse tools, which effectively tells the agent when to use this rather than hunting for per-type variants. It stops short of naming the remaining siblings (news_feed, theme_summary, brief) or stating when NOT to use it, so it falls short of a 5.

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