Results for “decision-logging”

Logs board meeting decisions with a two-layer memory architecture, separating raw transcripts from approved decisions, and provides commands to review past decisions and overdue action items.

Stop re-litigating decisions you already made. Keep a decision record where each entry captures the decision, the context that forced it, the options you weighed, why you chose, and when to revisit, one entry at a time, in plain searchable markdown you can grep later. Trigger on "log this decision", "why did we choose X", "write a decision record", "record why we're doing this", "what did we decide about", or any moment a real call gets made and would otherwise be forgotten.

Record durable project decisions with rationale, alternatives, assumptions, status, and revisit triggers. Load when the user says record this decision, we decided, decision log, why did we choose, revisit this later, or capture architectural/process rationale.

Two-layer memory architecture for board meeting decisions. Manages raw transcripts (Layer 1) and approved decisions (Layer 2). Use when logging decisions after a board meeting, reviewing past decisions with /cs:decisions, or checking overdue action items with /cs:review. Invoked automatically by the board-meeting skill after Phase 5 founder approval.

Use `task-agent` for bounded logging changes or `review-agent` to independently assess placement, schema, severity, redaction, correlation, and signal tradeoffs. Skip work with no logging impact and self-review requests.

Record decisions with rationale, alternatives, and consequences — the ADR pattern as a primitive. Use when a consequential choice is made — architecture, tooling, process, scope, trade-off. Capture WHY, not just WHAT.

Record a decision: finalized → ADR (optionally rule + guide or spec + plan); open proposal → RFC. Use for 'we decided', 'record this decision', 'make it a standard', 'draft an RFC', 'should we switch to Y'. Not for feature planning or documenting existing code.

【非推奨 → ssot-record を使うこと】 ssot-record に統合済み。/record-decision が呼ばれた場合は ssot-record スキルに処理を委譲する。

Create and maintain lightweight Architecture Decision Records as agent-readable decision memory — what was decided, why, and which alternatives were rejected. Use when "record this decision", "set up ADRs", "the agent keeps suggesting Y again". Docs vs code drift → plan-docs-sync. Session state → handoff.

An ADR records one decision at the moment it is made, with the information that

Produces auditable, schema-valid JSON decision records with assumptions, risks, recommendations, and review gating for high-stakes choices.

Save the current diagnosis state to disk for cross-session recall, including conclusions, rejected directions, and next steps.

Design and verify auditable human oversight, approval gates, escalation paths, and safe state transitions for AI agent workflows. Use when deciding which agent actions require review, adding approve/reject or dual-control flows, preventing unauthorized autonomous effects, creating decision records, reducing rubber-stamping, or recovering safely from rejected, expired, or failed actions.

Audit-ready decision artifacts for LLM outputs — assumptions, risks, recommendation, and review gating (schema-valid JSON).

Write a new ADR when a non-trivial or hard-to-reverse decision is made. Use for architecture, workflow, tooling, or policy decisions that should persist in docs/adr.

Structured logging strategy — levels, correlation IDs, context propagation, PII avoidance. Use when designing a logging approach, reviewing log statements, setting up log aggregation (ELK, Loki, CloudWatch), adding correlation IDs to a distributed system, or deciding what to log and what to keep out.

debug-logging

Creates and manages Architecture Decision Records using the Michael Nygard format, including new ADR creation, retrospective analysis, superseding, deprecating, and index generation.

Build ontology logs (ologs) from problem descriptions using categorical foundations. Use when designing problem taxonomies, classifying tasks for routing, building knowledge libraries, establishing formal analogies between domains via functor search, or translating between natural language and database schemas. NOT for OWL/RDF ontology work, query tuning, or graph modeling without functional-arrow discipline.

Standards for structured logging and observability in Golang. Use when adding structured logging or tracing to Go services.

Teaches how to write growth logs that extract reusable patterns from complex tasks, failures, and reviews, with templates and quality checks.

Write growth logs that extract reusable patterns from complex tasks, failures, and learning moments, using a structured template and quality checklist.

Diagnose your own behavior by reading the structured logs you leave behind — turns.jsonl, events.jsonl, chat_history.jsonl, scheduler.yaml. Use when something has gone wrong (a message didn't land, a scheduled job isn't firing, a communication pattern feels off), when you need to understand a pattern over many turns, or when cost / token usage needs auditing. Covers jq query recipes and points at the debugging-jobs / debugging-communication / debugging-drift companion guides for specific failure modes.

Reduce decision time and cognitive burden by limiting the number and complexity of simultaneous choices in user interfaces.

Records daily activities, progress, decisions, and learnings in structured chronological markdown files.

Query and filter Datadog logs from the shell using the Composio CLI. Run scoped log searches, pivot across services/environments, and export structured JSON for incident investigation and diagnostics.

Designs and reviews feedback loops for AI agents to ensure goals are machine-decidable, loops are damped, and human judgment is preserved.

Turns any long-running domain (business, relationships, health, career, learning, investing) into a local knowledge project with four layers, source tags, immutable snapshots, and a concept library that learns patterns over time.

Build logic models linking activities to impact. TRIGGERS - Use when user needs help with logic-model related tasks.

Use with analysis-agent or task-agent for task-local transaction, isolation, and conflict decisions. Do not use without a transaction decision or as task owner.

Use when selecting a statistical test with AI consultation, when assumptions need checking against the actual data, when an analysis plan or decision log must be written before running anything, or when results need APA-style reporting with effect sizes.

当需要进入并维持高度专注的深度工作状态时