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Veris

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identify_unverified_behaviors

Identifies untested code paths and behaviors in a repository, reporting coverage gaps, failing targets, and unverified assumptions to guide testing efforts.

Instructions

Returns verification coverage: how much of the planned work has supporting execution evidence, weighted by tier, decayed by age, and weighted by trust class (agent-asserted evidence counts for half). Also returns the count of failing and flaky targets, the highest single impacted-node risk, and the specific unverified assumptions (capped at 20). 'overallConfidence' is an alias of coverage retained for compatibility — it measures evidence, not the probability that the code is correct, and is not calibrated against observed outcomes. Coverage is reported as unknown, not 100%, when nothing was planned.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
executedTargetsCountNoWhat-if override: model coverage as if this many targets had been executed. Only applies when persistent state is unavailable.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv3.0.1
    • changedInput schema / properties / executedTargetsCount / description
      Previous value: -"Override the count of executed verification targets used in the math. Useful for what-if scenarios or when execution data lives outside Veris state.db."New value: +"What-if override: model coverage as if this many targets had been executed. Only applies when persistent state is unavailable."
  2. Changed1 schema field changedv2.1.10
    • addedInput schema / properties / executedTargetsCount / description
      Added value: +"Override the count of executed verification targets used in the math. Useful for what-if scenarios or when execution data lives outside Veris state.db."
  3. First observed

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden. It transparently explains output semantics (overallConfidence is an alias, not a probability; coverage is unknown when nothing planned), and details the what-if override behavior. It does not explicitly state side effects, but the read-only nature is implied by the 'returns' language.

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?

The description is dense but well-organized, packing necessary clarifications (alias meaning, weighting factors, edge cases) without redundancy. Every sentence adds value, and the structure flows logically from core functionality to caveats.

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

Completeness4/5

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

The description covers the main outputs and edge cases (unknown when nothing planned, what-if override scope). While it does not enumerate all possible response fields or error conditions, the essential context for a caller—what the tool computes and when to use the parameter—is adequately provided.

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

Parameters5/5

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

The single parameter executedTargetsCount has a clear, self-contained description explaining its purpose (what-if override) and its condition (only when persistent state is unavailable). Schema coverage is 100%, so no parameter is left undocumented.

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 the tool returns verification coverage and related metrics (failing/flaky counts, risk, unverified assumptions). It also clarifies the meaning of overallConfidence and the unknown-coverage edge case, making the purpose unambiguous and distinguishing it from sibling tools like analyze_repository or 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 Guidelines3/5

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

The description provides some usage context, notably that executedTargetsCount is a what-if override only applicable when persistent state is unavailable. However, it does not explicitly compare with sibling tools or state when to prefer this tool over alternatives, leaving some ambiguity about its role in a workflow.

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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