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identify_unverified_behaviors

Compute a confidence score for your repository by weighing real execution history with a 14-day half-life decay, and identify unverified behaviors that lack matching execution coverage to flag risky nodes.

Instructions

Returns an overall confidence score for the current repository plus the list of unverified behaviors (nodes flagged as risky but with no matching execution coverage). Confidence math weighs real execution history with a 14-day half-life decay — recent successful runs raise the score, recent failures or stale data lower it. Use this as the final readout after analyze_pr_behavior + generate_verification_plan, or as a gate in CI ('exit non-zero if confidence < 70'). Pass executedTargetsCount to model a what-if ('what would confidence be if 5 more targets were executed?').

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
executedTargetsCountNoOverride the count of executed verification targets used in the math. Useful for what-if scenarios or when execution data lives outside Veris state.db.
Behavior4/5

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

No annotations provided, so the description carries full burden. It details the confidence math with half-life decay and what affects scores. It does not mention side effects (likely read-only) or output format, but is fairly transparent about algorithm and parameter effect.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, well-structured with main purpose first, then details about confidence math and usage. No unnecessary words, every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema, but description explains return values (confidence score, unverified behaviors) and covers parameter usage comprehensively. Given tool complexity and context signals, the description is complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% (1 parameter). The description adds value beyond the schema by explaining 'executedTargetsCount' as an override for what-if scenarios and external data. Enhances understanding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it returns a confidence score and list of unverified behaviors. It specifies its role as a final readout after other tools or as a CI gate, distinguishing it from siblings like analyze_pr_behavior and generate_verification_plan.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says when to use: after analyze_pr_behavior + generate_verification_plan, or as a CI gate. Also describes the optional parameter for what-if scenarios. Does not explicitly state when not to use, but context is clear.

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

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