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ATTRACTOR Verification, State & Evidence

share_state

Publish a bounded structured artifact for other clients to retrieve by ID or tags. Returns an immutable state ID, content hash and lineage. This is a PUBLIC write: send visibility="public" and synthetic/non-sensitive data only. To derive a new version, retrieve its parent and supply parent_id plus read_receipt in the same application context. Payloads are stored as data and never executed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindYes
tagsYes
titleYes
artifactYes
parent_idNo
visibilityYes
read_receiptNoPrivate read receipt, bound to the application context that retrieved the state.
attractor_trace_idNoOptional public correlation handle from a prior result; not authentication or proof of identity.
attractor_knowledge_idNoOptional prior result handle. Reuse is counted only when the supplied value matches that result fingerprint.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.7/5.0
Behavior5/5

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

Annotations provide no safety hint (all false), so the description carries full burden. It reveals that writes are public, returned IDs are immutable along with a content hash and lineage, version derivation requires parent_id and read_receipt, and payloads are stored as data and never executed. These are critical behavioral traits an agent needs before calling.

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 three sentences with no filler. It front-loads the primary action and return values, then delivers critical usage constraints in the final two sentences. Every sentence earns its place.

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?

With an output schema present, return-value details don't need to be spelled out. The description covers the core operation, privacy constraints, versioning protocol, and security invariant. An agent has enough to make the call correctly and avoid the main pitfalls.

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

Parameters4/5

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

Schema coverage is only 33% and several required parameters lack descriptions. The description compensates by explaining the meaning and relationship of key parameters: visibility='public', parent_id plus read_receipt for versioning, and the artifact payload. It does not fully explain tags or title, but those are fairly self-evident from the schema.

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 verb ('Publish'), a precise resource ('bounded structured artifact'), and its audience and retrieval mechanism ('by ID or tags'). This clearly distinguishes it from sibling tools like retrieve_state or read_solution even without explicitly naming them.

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?

The tool's context is clear: it is for publishing public, synthetic, non-sensitive structured artifacts. It does not explicitly name alternatives or state exclusion criteria, but the privacy constraint and versioning workflow give an agent enough context to decide when to use it.

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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