turingmind_ingest_runtime_signal

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

Since no annotations are provided, the description fully bears the burden of behavioral disclosure. It details automatic threshold checks, confidence decay, node failure at 0.6, invalidation on regression, and evidence recording, providing extensive insight into the tool's effects.

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 concise (4 sentences), front-loaded with the main action, and every sentence adds meaningful information without redundancy. It is well-structured and earns its length.

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 the tool's complexity (7 params, no output schema), the description is comprehensive enough. It explains the flow of signal ingestion and the effects on nodes. It does not need to detail return values since 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 coverage is 100%, so baseline is 3. The description adds value by explaining parameter semantics beyond the schema, such as giving examples for 'value' (e.g., 0.04 for 4% error rate) and clarifying special behavior for 'signal_type' ('regression' fully invalidates).

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: ingesting a live runtime signal into the constraint graph. It uses specific verbs and resources and distinguishes itself from sibling tools by being the only one that handles runtime signals.

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 explicitly says 'Call from CI, Sentry, Datadog, or any monitoring source,' giving clear context on when to use the tool. While it doesn't list alternatives or when not to use it, no sibling tool serves a similar function, so the guidance is sufficient.

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