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AtlaSent-Systems-Inc

atlasent-mcp

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AtlaSent — VQP Verify Snapshot

atlasent_vqp_verify

Re-derives VQP prompt from snapshot bundle data, compares against stored hash to detect tampering, and optionally re-runs AI model to identify score drift. Records audit evidence for SOC 2 and 21 CFR Part 11 compliance.

Instructions

Re-derive the VQP prompt from current bundle data and verify it matches the stored SHA-256 prompt_hash. Detects tampering (hash_match: false) and optionally re-runs the AI model to detect score drift (score_delta, verdict_changed). Writes a vqp_audit_log row for SOC 2 CC7.2 / 21 CFR Part 11 evidence. Requires ATLASENT_SUPABASE_URL and ATLASENT_SUPABASE_SERVICE_ROLE_KEY.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rerunNoRe-call the AI model with the re-derived prompt to detect score drift. Populates rerun_score, rerun_verdict, score_delta. Slower (10–20 s AI call).
snapshot_idYesSnapshot ID from atlasent_vqp_generate or a stored vqp_snapshots row.
Behavior4/5

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

Annotations indicate readOnlyHint=false and destructiveHint=false but are generic. The description adds significant transparency: it discloses that the tool writes an audit log, optionally makes an AI call (10-20s slower), and detects tampering and drift. No contradiction with 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?

Four concise sentences, all essential. The main action is stated first, followed by detection capabilities, optional behavior, logging, and requirements. No filler or redundancy.

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?

Despite no output schema, the description mentions key outputs (hash_match, score_delta, verdict_changed, audit log row). It covers auth requirements and optional behavior. Could explicitly state return format but is sufficient for an agent to understand outcomes.

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 coverage is 100% with detailed descriptions for both parameters. The description reinforces the optional AI re-run (rerun) and the source of snapshot_id, adding context beyond the schema (e.g., '10–20 s AI call' for rerun). This warrants a score above baseline 3.

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 uses specific verbs ('re-derive', 'verify', 'detects', 'writes') and clearly identifies the resource (VQP snapshot). It explains the core verification of hash_match and optional drift detection, distinguishing it from sibling tools like atlasent_vqp_generate and atlasent_vqp_audit_summary.

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 states the required environment variables and implies use for tampering detection and SOC2/CFR compliance. It does not explicitly list when not to use or compare to alternatives, but the context is clear enough for a specialist tool.

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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