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mimaworks/governance-mcp

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by mimaworks

attest

Record AI governance actions as compliance evidence, mapping each event to EU AI Act, SOC 2, ISO 42001, and NIST AI RMF controls to create an audit trail and update your readiness score.

Instructions

Record a compliance evidence event in the Mima governance ledger, mapped to EU AI Act, SOC 2 Type II, ISO 42001, and NIST AI RMF controls.

Call this when the AI system performs a governance-relevant action that requires an audit trail: a human reviewing or overriding an AI decision, a risk assessment being completed, a model being evaluated for accuracy or bias, an access review, a policy being acknowledged, or an incident being reported.

Do NOT call this for routine AI inference calls — only for actions where a regulator or auditor would expect documented evidence.

Returns the record_id and the list of compliance controls earned (e.g. EUAIA_ART14, SOC2_CC6.1). The GRC manager sees these in the Mima governance dashboard and they count toward the readiness score.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
payloadYesEvent-specific fields. Unknown fields are stored but do not earn additional controls. For human_oversight: { decision, reviewer, outcome_summary, system_prompt_version? }. For ai_risk_assessment: { risk_level, risk_summary, art5_self_assessment?, mitigations? }. For model_evaluation: { accuracy, robustness_score?, bias_metrics?, evaluated_by? }. For incident_report: { severity, description, resolution? }.
identityNoUser or service identity performing the action. E.g. 'user@example.com'.
resourceNoThe resource or entity acted upon. E.g. 'customer-id:12345'.
environmentNoDeployment environment. Defaults to 'production' on the server side.
occurred_atNoISO 8601 timestamp of when the event occurred. Defaults to now.
record_typeYesThe governance event type. Maps to the SDK's 11 record types.
system_nameYesName of the AI system generating this record. E.g. 'loan-scoring-v2'. Alphanumeric, spaces, hyphens, underscores, and dots only.
enforce_gatesNoIf true, checks all required governance gates before writing. Recommended for production actions and high-risk systems. If a required gate is failing, the write is blocked — use dry_run_attest to confirm this record would earn controls that close the gap, then re-call attest without enforce_gates once you have verified the impact.
Behavior5/5

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

With no annotations, the description fully discloses behavior: it returns record_id and compliance controls earned, notes that unknown fields are stored but earn no controls, explains the enforce_gates blocking behavior, and states default values for environment and occurred_at. This goes well beyond the structured schema.

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 compact and well-structured, leading with the core purpose, then when to call, when not to call, and finally the return value. Every sentence carries meaningful information with no redundancy.

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 clearly explains the return value (record_id and controls) and how the records integrate with the governance dashboard. It also covers exclusions and gate-checking behavior, making it complete for this 8-parameter tool with no annotations.

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 description coverage is 100%, with rich descriptions for all 8 parameters. The main description adds no additional parameter-level semantics beyond what the schema already provides, so the baseline score of 3 is appropriate.

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 opens with a specific verb ('Record') and resource ('compliance evidence event in the Mima governance ledger'), and further specifies the compliance frameworks (EU AI Act, SOC 2, ISO 42001, NIST AI RMF). This clearly defines the tool's purpose and distinguishes it from siblings like dry_run_attest or check_gates.

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

Usage Guidelines5/5

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

The description provides explicit usage guidance: 'Call this when the AI system performs a governance-relevant action...' and 'Do NOT call this for routine AI inference calls'. It also names dry_run_attest as an alternative in the enforce_gates parameter description, giving clear when-to-use vs when-not-to-use direction.

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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