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sammyboi81

humane-intelligence

govern

Enforce pre-action approval with deterministic rules. Veto actions when trigger flags match, ensuring accountable AI behavior.

Instructions

Ask may-I before acting. Deterministic, zero-LLM: any rule whose trigger appears in flags vetoes. flags/rules accept lists or {name: true} / {trigger: action} maps.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
flagsNo
rulesNo
actionYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations, the description carries the burden. It does disclose key behavior: deterministic, zero-LLM, rule veto based on flags, and accepted list/map formats. However, it omits side effects (is it read-only?), error behavior, and what happens when no rule matches, which are important for safe invocation.

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?

Two sentences pack the core purpose and mechanism with no filler. The description is front-loaded with the main intent and then clarifies the rule logic, achieving high density without sacrificing clarity.

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?

The description covers the core logic and parameter formats but is incomplete for a tool with no output schema and no annotations. It doesn't state the return value (e.g., boolean approval), default behavior when no rule matches, or when to use this tool over siblings. These gaps would hinder an agent in making a fully informed call.

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 description coverage is 0%, so the description must explain the parameters. It effectively clarifies the flags and rules formats (lists or maps, with {name: true} / {trigger: action} examples) and the veto logic. The action parameter is left implicit but is required and self-explanatory. This is strong compensation for the schema gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description conveys a permission-checking role ('Ask may-I before acting') and explains the deterministic veto mechanism, but it lacks a clear verb-resource structure and doesn't differentiate itself from siblings like request_action or check_conformance. The purpose is inferable but not explicitly contrasted.

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?

The description implies when to use (before acting) but provides no explicit guidance on when to prefer this over sibling tools such as request_action, check_conformance, or validate_token. No alternatives or exclusions are mentioned, leaving the agent to guess.

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