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deep-agentic-core-mcp

deep-agentic-core-mcp

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by DeepAgentLabs
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Python
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Validate AI Operations Artifact

spec.validate_artifact
Read-only

Validates an AIOS artifact against the schema set named by its spec_version (v0.5 rules) and returns a conformance report citing AI Operations rule IDs separately from server presentation.

Instructions

Validate an AIOS artifact against the schema set its spec_version names (v0.5 compatibility rules), returning a conformance report that cites AI Operations rule IDs separately from server presentation.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "artifact": "<artifact>"
    },
    "name": "spec.validate_artifact"
  }
}

Input Schema

NameRequiredDescriptionDefault
artifactYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A3.5/5.0
Behavior3/5

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

readOnlyHint=true already tells the agent this is a non-mutating operation, so the description's added value is in disclosing that a conformance report is returned with AI Operations rule IDs cited separately from server presentation. That is useful output-shape context, but it says nothing about failure behavior for malformed artifacts, unsupported spec versions, or report verbosity.

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?

One front-loaded sentence with no filler; the validation target comes first and the return behavior second. The closing clause about rule IDs versus 'server presentation' is slightly opaque jargon, but nothing is redundant.

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?

Given a single nested-object parameter, no output schema, and annotations that already cover the safety profile, the description supplies the essentials: what is validated, against what, and roughly what comes back. Missing detail on artifact shape and failure modes keeps it short of full completeness.

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?

The single parameter is an untyped object with 0% schema description coverage, so the schema carries no semantics at all. The description partially compensates by revealing that the artifact is expected to carry a `spec_version` field that selects the governing schema set, but the rest of the artifact's expected structure remains undocumented in both places.

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 and resource ('Validate an AIOS artifact') plus the mechanism: validation runs against the schema set named by the artifact's `spec_version` under v0.5 compatibility rules. It does not distinguish itself from close siblings such as evals.validate_artifact, core.verify, or core.compatibility, so an agent cannot route between them on description alone.

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?

Usage is implied rather than stated: the description makes clear this is for checking artifact conformance to its declared spec version, but never says when to prefer it over evals.validate_artifact, core.verify, or core.compatibility, nor what preconditions the artifact must meet. No exclusions or alternative routing are given.

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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