chainvectorPredictionsStability

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

With no annotations, the description carries the full burden. It transparently explains what the scores mean (0-100 for stability, -100..+100 for momentum, 30s/1m/5m windows) and the behavioral interpretation. It does not cover edge cases like missing data or error conditions, but for a read-only analytical tool, the provided context is strong.

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 two sentences with no wasted words. The first sentence packs the metric definitions and window options; the second provides actionable guidance. It is front-loaded and efficient.

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?

There is no output schema, so the description must explain return values. It fully covers the score names, ranges, semantics, and time windows. Given only two straightforward parameters, the description is complete for selecting and invoking the tool.

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%: venue and market_id are already self-explanatory. The description adds no further parameter-specific meaning beyond the schema, so baseline 3 is appropriate.

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 specifies the tool's focus: 'ChainVector prediction bid-price stability for one market'. It defines the core outputs (stability_score and momentum_score) with ranges and meanings, which distinguishes it from sibling tools like chainvectorPredictionsQuotes or chainvectorMomentum by targeting bid-price stability specifically.

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 provides a clear decision rule: 'A churning or adversely-repricing quote is an entry veto.' This implies using the tool as a pre-entry stability check and indicates when to avoid entering. However, it does not explicitly discuss alternatives or when-not-to-use scenarios relative to sibling tools.

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