get_analyst_recommendations

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

Annotations already cover safety (readOnly, idempotent, non-destructive, openWorld), so the bar is lower, and the description still adds real behavior: default Markdown vs JSON output, N/A fields returned for uncovered stocks, and short error messages rather than exceptions. The only gap is freshness/recency of analyst data and any rate-limit or pagination behavior, which are not addressed.

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?

Front-loaded with purpose, then usage and exclusions, then output behavior – a logical progression that an agent can scan. Slightly redundant in re-announcing the Markdown default after the schema already declares it, but no wasted sentences of any consequence.

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 read-only lookup with an output schema, the description covers everything the agent needs: what comes back, the format switch, the no-coverage edge case, and the sibling boundaries. Even though an output schema exists, the N/A and error-message notes preempt the two failure modes an agent would otherwise misread.

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 both parameters are already documented in structured fields; the description's mention of "response_format='json'" merely restates the schema. No additional meaning is added for the ticker beyond the schema's format hints, so the baseline of 3 applies.

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?

"Wall Street analyst view on one stock" is a specific verb+resource, immediately followed by an enumeration of the payload (price targets high/mean/low, consensus rating, buy/hold/sell trend, recent upgrades/downgrades). It is unmistakably distinct from siblings like get_analyst_estimates or get_holders without opening any schema.

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 an explicit trigger phrase ("what do analysts think of X", ratings, sentiment) and names two alternatives with the exact boundary conditions: get_analyst_estimates for forward EPS/revenue/growth numbers, get_market_news for news-driven sentiment. It even adds a data-quality caveat about thin small-cap coverage that tells the agent when to discount results.

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