get_expert_intelligence

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

Annotations already disclose readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description does add non-obvious operational context (1 registry lookup + 8 parallel Cypher queries + 1 merge pass), which hints at fan-out cost and latency. However, it omits the behavioral fact that actually matters for selection: that this is a legacy alias of get_specialist_intelligence.

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?

Two compact sentences with the primary capability front-loaded and no filler. The parenthetical pipeline detail is borderline noise for an agent choosing a tool, but it is short and does not obscure the main clause.

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 six-parameter search tool with no output schema, the description should at least explain what comes back conceptually (trends, evidence bundles) and warn that it is a legacy alias. It does neither, and the annotation-only signal about aliasing would be invisible to an agent reading the description alone.

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% with all six parameters (query, limit, min_score, include_evidence, max_evidence_per_trend, userId) documented in the schema itself. The description adds no parameter-level detail such as query syntax expectations or how min_score interacts with limit, 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?

The description states a recognizable action ('parallel search across ... frameworks and ... specialist strategist graphs'), but the vocabulary ('strategist agency frameworks', 'specialist strategist graphs') does not match the tool name ('expert') or the annotation title ('Specialist Intelligence'), leaving the actual resource ambiguous. It also never distinguishes itself from the sibling tool 'get_specialist_intelligence', which the annotations imply it aliases.

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?

There is no when-to-use guidance, no prerequisites, and no mention of alternatives such as get_specialist_intelligence, search_graph, or get_domain_intelligence. Since the annotation title labels this a 'Legacy Alias', the absence of any routing note to the canonical tool is a meaningful omission.

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