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AtlaSent-Systems-Inc

atlasent-mcp

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AtlaSent — VQP Generate Snapshot

atlasent_vqp_generate

Score a constraint bundle against six VQP criteria (access control, audit coverage, escalation paths, deny specificity, hold conditions, override governance) and store a tamper-evident snapshot with a SHA-256 prompt hash.

Instructions

Score a constraint bundle against the 6 VQP criteria (access_control CC6.1, audit_coverage CC7.2, escalation_paths CC7.4, deny_specificity CC8.1, hold_conditions CC6.3, override_governance CC5.2). Stores a tamper-evident snapshot with a SHA-256 prompt_hash in vqp_snapshots. Verdicts: qualified (≥85, no fails), conditionally_qualified (≥60), not_qualified. Requires ATLASENT_SUPABASE_URL and ATLASENT_SUPABASE_SERVICE_ROLE_KEY.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
org_idYesOrganization ID that owns the bundle.
bundle_idYesConstraint bundle ID to score.
vqp_contextNoAdditional context embedded in the VQP prompt for this snapshot.
Behavior3/5

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

Annotations indicate non-read-only and non-destructive behavior. The description adds context by stating that a snapshot is stored and requires specific environment variables. However, it does not elaborate on potential side effects, idempotency, or data retention policies, leaving some behavioral aspects undisclosed beyond annotations.

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 two sentences, front-loading the primary action. Every sentence provides necessary information with no extraneous content. The format is efficient and clear.

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 explains the core action and verdicts but lacks detail on the output format or return value. It does not document the vqp_context parameter's usage. Given moderate complexity and no output schema, the description is adequate but leaves gaps that could hinder an agent's correct invocation.

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

Parameters3/5

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

Schema coverage is 100%, so the baseline is 3. The description adds overarching context about VQP criteria and verdict thresholds but does not provide additional parameter-specific meaning beyond the schema. It does not explain how vqp_context is used or what values it should contain.

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?

The description clearly states the tool scores a constraint bundle against six specific VQP criteria and stores a tamper-evident snapshot. It uses specific verbs ('Score', 'Stores') and identifies the resource ('constraint bundle', 'vqp_snapshots'). However, it does not differentiate this tool from sibling VQP tools like atlasent_vqp_audit_summary or atlasent_vqp_verify.

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 provides no guidance on when to use this tool versus alternatives. It lacks explicit context for when the tool is appropriate, prerequisites beyond environment variables, and does not mention any exclusionary or comparative criteria.

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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