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simarch_form_organization

Creates a contract-bound autonomous AI organization with roles, authority, contracts, and tool permissions from a mission objective and chosen scale.

Instructions

Synthesizes an autonomous AI organization with roles, contracts, authority, and tool permissions from an objective.

Input Schema

NameRequiredDescriptionDefault
nameYesOrganization name
scaleNoauto
objectiveYesHigh level mission statement

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior3/5

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

With no annotations at all, the description carries the full burden, and it does disclose the artifacts produced (roles, contracts, authority, tool permissions) — useful context the schema does not provide. However, it omits whether the organization is persisted, whether an existing one is overwritten, whether generation is LLM-driven/non-deterministic, and what the response returns.

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?

A single dense sentence that front-loads the verb and enumerates the outputs. No filler, no repetition of the tool name.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 3-parameter generation tool with no annotations and no output schema, the description gives a reasonable picture of what is produced but leaves the return shape, persistence semantics, and the meaning of "scale" unexplained. An agent can call it, but not predict the cost or result.

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

Parameters2/5

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

Schema coverage is only 67% and the uncovered parameter is the important one: "scale" (auto/compact/standard/enterprise) has no description in either the schema or the description text. The description only implicitly evokes "objective" ("from an objective") and says nothing about how name or scale shape the synthesized organization.

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 ("Synthesizes") and a specific resource ("an autonomous AI organization with roles, contracts, authority, and tool permissions"), plus the input it derives from ("an objective"). The purpose is clearly distinct from siblings like simarch_run_simulation or simarch_evaluate_decision, though the description never names or contrasts them.

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

Usage Guidelines2/5

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

There is no statement of when this should be invoked versus alternatives such as simarch_run_simulation, nor any prerequisite or exclusion. The reader can infer it is a setup/formation step, but nothing in the text confirms sequencing or conditions.

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