fahali_get_highest_conviction_signals

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

With no annotations, the description fully discloses behavioral traits: it returns aggregated consensus signals, details the entry fields (engine list, severity, direction, timestamp, provenance), validates engine names against a canonical registry, and states it is public. No destructive side effects are implied. This is thorough.

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 consists of two concise sentences: the first states the purpose and output, the second details the entry fields and validation. No unnecessary words, and key information is front-loaded.

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 no parameters and no output schema, the description adequately explains what the tool does and returns. It covers the consensus logic, field details, and access. It does not mention limits or pagination, but for a simple retrieval tool, this is sufficient.

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?

There are no parameters, and schema coverage is 100%, so the description does not need to add parameter information. Baseline 4 is appropriate, and the description adds context about the returned data structure, which is helpful.

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 purpose: 'Get highest-conviction multi-engine consensus signals.' It describes what is returned: symbols with 2+ engines agreeing, ranked by engine count and directional decisiveness. This distinguishes it from siblings like fahali_get_contagion_map which focus on different aspects.

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 mentions 'Public data — no tier required,' indicating accessibility, but does not provide guidance on when to use this tool versus alternatives like fahali_get_market_sentiment or fahali_get_engine_status. There is no 'when-not-to-use' or explicit recommendation.

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