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mcp_aql_create

Create new AI personas, skills, templates, agents, memories, or ensembles and append entries without overwriting existing data. Use it to add elements and records safely.

Instructions

Additive, non-destructive operations.

Supported operations: create_element, import_element, addEntry, verify_challenge, release_deadlock, beetlejuice_beetlejuice_beetlejuice, record_execution_step, install_collection_content, submit_collection_content, init_portfolio, sync_portfolio, portfolio_element_manager, setup_github_auth, configure_oauth, import_persona

Element types: persona, skill, template, agent, memory, ensemble

These operations add new data without removing or overwriting existing content.

Quick start examples: { operation: "create_element", element_type: "persona", params: { element_name: "MyPersona", description: "A helpful assistant", instructions: "You ARE a helpful assistant. ALWAYS provide clear, accurate responses." } } { operation: "create_element", element_type: "agent", params: { element_name: "MyAgent", description: "Task executor", instructions: "Execute goals methodically. Report progress at each step.", goal: { template: "Complete: {objective}", parameters: [{ name: "objective", type: "string", required: true }] } } } { operation: "create_element", element_type: "memory", params: { element_name: "session-notes", description: "Session context and notes" } } { operation: "create_element", element_type: "ensemble", params: { element_name: "my-ensemble", description: "Combined element set", metadata: { elements: [{ element_name: "expert", element_type: "persona", role: "primary" }, { element_name: "analysis", element_type: "skill", role: "support" }] } } } Valid ensemble roles: primary, support, override, monitor, core { operation: "addEntry", params: { element_name: "session-notes", content: "Remember this fact", tags: ["important"] } } Note: addEntry content supports markdown (headers, lists, bold, tables, code blocks). Ensure markdown content is properly JSON-escaped — use \n for newlines, " for quotes, and \ for backslashes within the JSON string value.

Execution lifecycle — record agent progress (appends step records, like addEntry): { operation: "record_execution_step", params: { element_name: "code-reviewer", stepDescription: "Analyzed files", outcome: "success", findings: "Found 3 issues" } } This is the normal next lifecycle call after mcp_aql_execute { operation: "execute_agent", ... }. Response flow: record_execution_step returns { autonomy: { continue, factors, notifications? } }. Check autonomy.continue to decide whether to proceed. Check autonomy.notifications for permission_pending (gatekeeper blocks), autonomy_pause, or danger_zone alerts to relay to human operators.

Import & portfolio: { operation: "import_element", element_type: "skill", params: { element_name: "code-formatter", data: "..." } } { operation: "import_persona", params: { source: "/path/to/persona.md" } } { operation: "install_collection_content", params: { element_type: "persona", element_name: "Creative-Writer" } } { operation: "submit_collection_content", params: { element_type: "skill", element_name: "code-formatter" } } { operation: "init_portfolio" } { operation: "sync_portfolio" } { operation: "portfolio_element_manager", params: { action: "push", element_type: "persona", element_name: "Tech-Writer" } }

Auth & verification: { operation: "setup_github_auth" } { operation: "configure_oauth", params: { client_id: "your-client-id" } } { operation: "verify_challenge", params: { code: "ABC123" } } { operation: "release_deadlock" } { operation: "beetlejuice_beetlejuice_beetlejuice" }

Batch operations: Use the operations array to execute multiple operations sequentially in a single request. { operations: [{ operation: "addEntry", params: { element_name: "log", content: "Step 1" } }, { operation: "addEntry", params: { element_name: "log", content: "Step 2" } }] }

Discover required parameters — use mcp_aql_read: { operation: "introspect", params: { query: "operations", name: "create_element" } } Discover element format specs (required fields, syntax, examples) — use mcp_aql_read: { operation: "introspect", params: { query: "format", name: "template" } }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsNoOperation parameters
operationYesOperation name to execute
operationsNoArray of operations for batch execution
element_typeNoTarget element type (optional)
Behavior5/5

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

Annotations only state readOnlyHint=false and destructiveHint=false. The description adds substantial behavioral detail: operations are non-destructive and additive; record_execution_step appends records and returns an autonomy object with continue, factors, and notifications; batch operations execute sequentially; and markdown content must be JSON-escaped. This goes well beyond the annotations and is consistent with them.

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 description is long but well organized into clear sections: core scope, element types, quick start examples, execution lifecycle, import/portfolio, auth, batch operations, and introspection. It is front-loaded with the most important semantic constraint. Some examples could be trimmed, but the length is largely justified for a multi-operation facade tool.

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?

This is a complex polymorphic tool with a thin schema, no output schema, and a large set of operations. The description covers operation categories, element types, parameter discovery, batch behavior, and the response flow for the lifecycle operation. It does not explain return shapes for most operations, but given the breadth and the explicit pointer to mcp_aql_read for discovering formats, the description is reasonably complete.

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?

The schema has 100% description coverage, but the descriptions are generic ('Operation parameters', 'Operation name to execute'). The tool description compensates by listing valid operation names, giving concrete params examples for create_element, addEntry, record_execution_step, and portfolio operations, and explaining the operations array for batch execution. It does not document every operation's full parameter set, but it explicitly directs the agent to use mcp_aql_read for introspection.

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 opens with 'Additive, non-destructive operations' and immediately enumerates the supported operations and element types. It clearly states that these operations add new data without removing or overwriting existing content, which differentiates this tool from its update/delete/execute siblings even without seeing their schemas.

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 description gives strong usage context: it distinguishes additive operations from non-additive ones, provides examples for common operation classes, and explicitly directs the agent to mcp_aql_read for discovering required parameters and element format specs. It also frames record_execution_step as the expected follow-up after mcp_aql_execute. It does not enumerate every 'when not to use' scenario relative to siblings, but the guidance is clear and actionable.

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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