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AtlaSent-Systems-Inc

atlasent-mcp

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Lookup Canonical Action Spec

atlasent_lookup_action
Read-only

Look up canonical action specifications from the Authorization Intelligence Library. Find gate flags, risk posture, and regulatory mappings for governed action types using slug or query.

Instructions

Look up canonical action specifications from the Authorization Intelligence Library. Returns gate flags (requires_human_approval, requires_mfa, requires_verified_actor, requires_state_snapshot), authorization patterns, risk posture, AI risk classification, regulatory mappings, and evidence requirements for any of the 17 governed action types. Use slug for an exact match (e.g. 'production.deploy') or query for a substring search across slug, display_name, and description. Omit both to list all 17 canonical actions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugNoExact canonical action slug (e.g. 'production.deploy', 'access.grant').
queryNoSubstring search across slug, display_name, and description. Case-insensitive.
Behavior4/5

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

Annotations already indicate readOnlyHint=true, but the description adds valuable detail about the return fields (gate flags, authorization patterns, etc.) and search behavior. It does not contradict annotations and provides behavioral context beyond what annotations offer.

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 concise, consisting of three sentences that are front-loaded with the main purpose. Every sentence adds value without redundancy or unnecessary words.

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?

Despite lacking an output schema, the description fully explains the return values (gate flags, authorization patterns, etc.) and the extent of the data (17 actions). It covers the two parameters and the behavior when they are omitted, making the tool's functionality complete for an AI agent.

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 100% (both parameters have descriptions). The description adds meaning by clarifying the use of 'slug' for exact match and 'query' for substring search, and that omitting both lists all actions. This goes beyond the schema descriptions, justifying a score above baseline.

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 clearly states the tool's purpose: 'Look up canonical action specifications from the Authorization Intelligence Library.' It specifies what is returned (gate flags, authorization patterns, etc.) and the scope (17 governed action types), distinguishing it from sibling tools that perform create, delete, or update operations.

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 explains when to use the tool ('for any of the 17 governed action types') and how to use the parameters (exact slug match, substring query, or omit to list all). However, it does not explicitly mention when not to use it or suggest alternative tools, though the context of sibling tools makes the usage relatively clear.

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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