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submit_attempt_verdict

Record a fix-verifier's verdict on a fix attempt: fix_confirmed, fix_failed, or partial. Confirmed fixes need a commit hash; partial results spawn a child finding for remaining work.

Instructions

Audit-plan: the fix-verifier's verdict on a fixer's attempt. verdict ∈ {fix_confirmed, fix_failed, partial}. On fix_confirmed, commit_hash is required and the finding moves to fixed. On fix_failed below retry cap, the finding moves to fix_failed (still claimable). On partial, the server auto-creates a child finding for the remaining work.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
VerdictNo
EvidenceNo
as_agentNo
AttemptIdYes
CommitHashNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden, and it does a good job: it discloses the state transitions the call triggers, the conditional commit_hash requirement, the retry cap, and the auto-creation of a child finding. It omits authorization/role constraints and the meaning of as_agent, but the mutation side effects are unusually well documented.

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?

Four tightly packed sentences, each earning its place: the first frames the tool, and the rest enumerate verdict-specific behavior. Front-loaded and free of filler.

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?

For a state-machine mutation with no output schema and no annotations, the description covers the outcome of each verdict and the conditional parameter requirement. The main gap is the unexplained Evidence object and as_agent parameter, which an agent would still need to infer.

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

Parameters3/5

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

Schema description coverage is 0% with 5 params, so the description must compensate. It adds real meaning for Verdict (enumerates the three allowed values the schema does not) and CommitHash (required only on fix_confirmed), but Evidence (a nested object), as_agent, and AttemptId are left entirely unexplained.

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

Purpose4/5

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

States a specific verb+resource ('the fix-verifier's verdict on a fixer's attempt') and situates it in the audit plan workflow, so the agent knows this is submitting a verifier judgement, not a fix or a review decision. It does not explicitly name how it differs from siblings like submit_verification_verdict or submit_review_decision, but the role phrasing is specific enough to distinguish it.

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?

Gives clear conditional context: which verdict value yields which outcome (fix_confirmed→fixed, fix_failed below retry cap→still claimable, partial→child finding). This tells the agent when each verdict applies and what state results. It stops short of naming alternatives or prerequisites (e.g., who may call it, when it is invalid).

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