# The algo records whose force is security_governance

This index as JSON: https://banes-lab.com/json/api/facets/algo/force/security-governance

## Entries

- [Conflict and Tension Resolution](https://banes-lab.com/records/algo/conflict-and-tension-resolution.md): For each selected concept, collect conflicts and tensions, classify conflicts as prohibitive or resolvable, classify tensions as trade-offs, and require an explicit decision when severity or impact is high.
- [Severity Policy](https://banes-lab.com/records/algo/severity-policy.md): Interpret severity as an enforcement policy: mandatory concepts become gates, recommended concepts become review findings, contextual concepts require scope justification, and discouraged concepts require explicit exception approval.
- [Domain Boundary Governance](https://banes-lab.com/records/algo/domain-boundary-governance.md): Identify bounded contexts, ubiquitous language, context relationships, domain model ownership, anti-corruption layers, and explicit boundary rules.
- [Security Governance](https://banes-lab.com/records/algo/security-governance.md): Threat-model the system, reduce attack surface, authenticate identity, authorize actions, validate input, encode output, encrypt data, manage secrets, enforce policy as code, and continuously audit compliance.
- [Architecture Evolution Governance](https://banes-lab.com/records/algo/architecture-evolution-governance.md): Assess architecture against quality attributes, document decisions, analyze impact, track gaps, define fitness functions, standardize patterns, and evolve through ADR-backed controlled change.
- [Control Plane Coordination](https://banes-lab.com/records/algo/control-plane-coordination.md): Separate control-plane policy from data-plane execution, centralize configuration, authentication, logging, or orchestration only where shared governance is beneficial, and preserve local autonomy where decentralization is required.
- [Model Architecture Governance](https://banes-lab.com/records/algo/model-lifecycle-governance.md): Register models, prompts, datasets, embeddings, retrieval sources, knowledge graphs, inference contracts, evaluation suites, explainability traces, safety gates, and monitoring policies.
- [Architecture Catalog Compiler](https://banes-lab.com/records/algo/architecture-catalog-compiler.md): Compile the relationship catalog into four executable artifacts: assessment rules, refactor playbooks, decision-support graphs, and governance gates.
- [Master Architecture Governance Kernel](https://banes-lab.com/records/algo/master-architecture-governance-kernel.md): Parse the catalog, validate records, build the graph, classify target scope, select relevant concept clusters, compute dependency closure, detect violations, measure evidence, resolve conflicts, generate refactor plans, enforce gates, and record decisions.
- [Architectural Contract Kernel](https://banes-lab.com/records/algo/architectural-contract-kernel.md): For any programmatic system, identify architectural concerns, define explicit contracts for each concern, bind implementations to those contracts, validate invariants, observe behavior, and evolve through versioned change.
- [Error Boundary](https://banes-lab.com/records/algo/error-boundary.md): Detect invalid state early, fail fast for programmer errors, fail safe for recoverable runtime faults, fail secure for security-sensitive failures, and return typed errors.
- [Security Policy](https://banes-lab.com/records/algo/security-policy.md): Threat-model the system, reduce attack surface, authenticate identity, authorize actions, validate input, encode output, encrypt data, protect secrets, and enforce policy continuously.
- [Governance Evolution](https://banes-lab.com/records/algo/governance-evolution.md): Assess architecture against quality attributes, record decisions, analyze impact, enforce standards with fitness functions, and evolve through documented change.
- [Control Plane](https://banes-lab.com/records/algo/control-plane.md): Separate control concerns from data execution, centralize policy/configuration/authentication/logging where beneficial, and decentralize runtime execution where autonomy is required.
- [Model Lifecycle Governance](https://banes-lab.com/records/algo/ai-model-governance.md): Register models and datasets, version prompts and artifacts, evaluate behavior against benchmarks, validate safety constraints, trace inference inputs, and monitor drift after deployment.
- [Developer Decision Gate](https://banes-lab.com/records/algo/developer-decision-gate.md): Request the developer's decision before destructive, ambiguous, conflict-prone, additive-with-debt, or high-risk actions, then bind the selected decision into subsequent plan state.
- [Trust Anchor](https://banes-lab.com/records/algo/trust-anchor.md): Classify every input by trust level — source files, schema/config/data, build and validator output, tool output, and structured logs are trusted; narrative docs, comments, prior codebase knowledge, and unverified claims are untrusted and require verification before use.
- [Cross-Cutting Surface Coverage](https://banes-lab.com/records/algo/cross-cutting-surface-coverage.md): Gate the software surface beyond structure — security, performance, infrastructure and deployment, and resilience — so a change's threat, budget, config, and failure consequences are covered, not only its structural ones.
- [Checklist Creation Kernel](https://banes-lab.com/records/algo/checklist-creation-kernel.md): Run the six-stage generator in order — orientation, planning, compilation, validation, repair, and rendering — bound by the cross-stage invariants, compiling a task description into a validated, dependency-aware execution checklist or an evidence-bearing blocked report.
- [<Checklist Governance Concern>](https://banes-lab.com/records/algo/checklist-governance-concern.md): <Orient on authority + evidence> → <Plan principles + protocols + dependency graph> → <Compile atomic tasks + ripple chains> → <Validate reasoning by evidence + semantic policy> → <Repair from the earliest invalid stage> → <Render one bounded terminal>
- [Recursion Control](https://banes-lab.com/records/algo/recursion-control.md): Increment depth on recursive entry, compare against maximum depth, reject excessive recursion, and unwind depth on completion.
- [Phase Close Gate](https://banes-lab.com/records/algo/phase-close-gate.md): Make completion a gated state of the plan rather than a judgment call — a phase closes only when all tasks are done, a dry reconciliation pass holds, verify is clean for the chosen scope, and the coverage graph confirms the ripple set; otherwise the loop returns to execution.
- [Plan Phase Verification](https://banes-lab.com/records/algo/plan-phase-verification.md): Before a composed plan reaches the developer, the engine loops it back through evidence, completeness, and adversarial-skepticism passes, reconciles the findings into the plan, and increments a loop-owned pass counter the model cannot forge; a render boundary blocks an unverified plan.
- [Governed Autonomous Plan Loop](https://banes-lab.com/records/algo/governed-autonomous-plan-loop.md): Drive a large task to completion under gates — seed per phase, investigate, execute, self-inform from canon and self-audit, capture considerations, reconcile at the boundary, and close only when the plan is a mechanically resolved state, then re-seed the next phase.
- [<Governed Plan Concern>](https://banes-lab.com/records/algo/governed-plan-concern.md): <Seed the phase> → <Investigate and execute under gates> → <Self-inform from canon and self-audit> → <Capture and reconcile considerations at the boundary> → <Close only on a mechanically resolved gated state> → <Re-seed the next phase>
- [Version Provenance](https://banes-lab.com/records/algo/version-provenance.md): Specializing Governance Evolution, detect whether the merge changed state, and only on real change bump the version, timestamp it, and append a modification record — leaving a no-op untouched.
- [Loop-Owned Mode Selection](https://banes-lab.com/records/algo/loop-owned-mode-selection.md): The loop assigns the (phase, activity) mode that selects which contract a response is validated against; the model's output carries no contract-selecting field, so a model can never grade itself against a contract it chose.
- [<Mode-Driven Response Schema>](https://banes-lab.com/records/algo/mode-driven-response-schema.md): Make the model's structured output a mode-driven composed contract — the output mirror of composed input context: per loop-owned mode the schema and instruction are projected from one field registry, the response is validated and self-heals against it, the typed fields are governed, and every turn is persisted as a versioned queryable record — so the output has one source, cannot drift from its instruction, and can be audited.
- [PAG Invariant Record](https://banes-lab.com/records/algo/pag-constraint-boundary.md): State every behavioural invariant as a record with four slots: the property in a form that could be false, the set it quantifies over, the parties it binds, and the objector, the check that would disagree if the property stopped holding or none as declared debt, so an unwatched invariant is visible rather than assumed.
- [Quality Governance Loop](https://banes-lab.com/records/algo/quality-governance-loop.md): On each update (an apply), normalize the proposal, resolve a CheckPlan, verify it, and on failure fix-then-reverify the downstream set until the verdict is clean or the pass bound is reached, then escalate.
- [Quality-Engine Kernel](https://banes-lab.com/records/algo/quality-engine-concern.md): Resolve a canonical policy into a per-ecosystem CheckPlan, order its stages by the invalidates relation, normalize the proposal, run generation checks on the server and project tools via the relay, derive a machine verdict, and drive a bounded downstream cascade to clean — holding no runtime execution in the engine itself.