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0pstech

kr.ai.vdb/vdb

by 0pstech

vdb_harden_verify

Verifies a patched file by re-abstracting it and checking the originally issued path, producing signed evidence tied to the analysis, IR fingerprint, and dependency graph.

Instructions

After applying a fix returned by vdb_harden, re-abstract the local file and verify the originally issued path. Returns a signed evidence payload bound to the original analysis, the fixed IR fingerprint, and the dependency graph. This proves VDB's decision over the submitted abstraction, not that the abstraction matches a deployed binary.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYesFixed Python file.
path_idYesPath id issued by vdb_harden.
manifest_pathYesThe same resolved manifest used for vdb_harden.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries the burden and does substantial work: it explains the signed payload, the binding to original analysis, IR fingerprint, dependency graph, and crucially clarifies the limitation ('not that the abstraction matches a deployed binary'). It does not state whether the tool modifies the local file or any side effects, but the read/verify nature is implied and the proof semantics are well disclosed.

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 with no wasted words. The first sentence front-loads the action and prerequisite, the second describes the output, and the third clarifies the proof's scope. Every sentence adds necessary meaning.

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?

Given no output schema and no annotations, the description explains the return payload contents and the intended interpretation. It ties to vdb_harden and the schema already covers parameter origins. The tool's purpose, workflow, output, and limitations are all addressed sufficiently for correct invocation.

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 coverage is 100%: all three parameters (path, manifest_path, path_id) already have descriptions in the schema. The description adds workflow context (e.g., 'fixed file', 'same resolved manifest'), but does not add substantial parameter-level semantics beyond the schema, so baseline 3 applies.

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 states a specific action ('re-abstract the local file and verify the originally issued path') tied to a clear workflow step after vdb_harden. It distinguishes itself from siblings by referencing the exact fix-return flow and explicitly scoping what the verification does and does not prove.

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?

It gives a clear context of when to use the tool ('After applying a fix returned by vdb_harden'), which orients the agent to the correct point in the workflow. It does not explicitly name alternative tools or list when-not-to-use conditions, but the context is strong enough for proper selection.

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