Kibi

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kb_ingest_proof

Destructive

Ingest a producer-emitted proof-run artifact and evaluate it against test proof contracts, then append idempotent proof receipts after validating snapshots, commands, outcomes, and history.

Instructions

Ingest a producer-emitted kibi.proof-run.v1 artifact and evaluate it against each selected test's kibi.proof-contract.v1 proof obligations. Revalidates the live workspace snapshot, integration command binding, run-level outcome, attempt history, success policy, and append-only proof-receipt history before deriving and appending idempotent kibi.proof-receipt.v1 receipts. Producers report what happened; Kibi evaluates proof. Prefer kibi prove so the configured producer runs automatically; direct ingestion is an integration path for custom producers and agents.

Input Schema

Name	Required	Description
`testIds`	No	Existing test entities with proof_contract.v1. Omit to evaluate every test contracted to the artifact's integration.
`artifact`	Yes	Producer-emitted kibi.proof-run.v1 proof artifact. Producers report what happened; Kibi evaluates proof obligations and policies. Produce it via `kibi prove` or direct kb_ingest_proof calls.
`snapshot`	Yes	Workspace snapshot captured immediately before the run.
`workspaceRoot`	No	Optional absolute path of the workspace this call is about when it differs from the one the server started in, for example the git worktree you are working in. The server answers from that workspace's knowledge base when it is a worktree of the same repository or lies under the client's MCP roots; otherwise it answers from its own workspace and adds a workspace_mismatch diagnostic. Host hooks fill this in automatically where available.

Output Schema

Name	Required	Description	Default
`data`	Yes
`error`	No
`status`	Yes
`effects`	Yes
`operation`	Yes
`diagnostics`	Yes
`nextActions`	Yes
`kibiProtocol`	Yes
`resultVersion`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedv0.1.4Oct 26, 2026

addedInput schema / properties / artifact / properties / certificates

Added value: +{
+  "description": "kibi.code-certificate.v1 objects the run left for certificate-kind contracts, one per test. Kibi re-checks each before a receipt counts as proved.",
+  "items": {
+    "additionalProperties": {},
+    "properties": {},
+    "type": "object"
+  },
+  "maxItems": 1000,
+  "type": "array"
+}

First observedv0.1.0Oct 17, 2026

TDQS

A4.4/5.0

Behavior4/5

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

While annotations cover high-level hints (destructive, readOnly), the description adds critical behavioral context by explaining the internal evaluation flow: it 'Revalidates the live workspace snapshot, integration command binding, run-level outcome, attempt history, success policy, and append-only proof-receipt history' before deriving receipts. This adds value beyond the hints.

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

Conciseness4/5

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

The definition is relatively dense, but the information is tightly packed and logically ordered: Function -> Process Detail -> Usage Policy. The sentences are highly information-rich and avoid fluff.

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 the complexity of the input schema (multiple nested objects, version constraints) and the detailed process described in the text, the definition is extremely complete. An AI agent has all the necessary information for accurate selection and 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?

Since schema coverage is 100%, the parameters are thoroughly defined structurally. The description does not need to elaborate on parameter meanings, focusing instead on the high-level context (e.g., the artifact being 'producer-emitted'). Baseline 3 is appropriate due to high schema coverage.

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 explicitly states the tool ingests a specific artifact ('kibi.proof-run.v1') and its core purpose is to evaluate it against specific proof obligations ('kibi.proof-contract.v1'). It clearly defines the operational scope of the function.

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

Usage Guidelines5/5

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

It provides excellent usage guidance by offering a clear hierarchy of preference: 'Prefer `kibi prove` so the configured producer runs automatically.' It then specifies the niche use case for this tool ('direct ingestion is an integration path for custom producers and agents').

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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