Results for “goodwill-policy”

Create, apply, and manage AgentRC policies to customize readiness scoring, disable checks, override impact levels, set pass-rate thresholds, and enforce CI gating.

Use to design support incentives that improve behaviour without destroying the metric — pairing pay with guardrails, naming gaming modes, and choosing measures that survive Goodhart pressure. Trigger for "incentive plan", "agent bonus scheme", "SPIFF design", "pay for QA score", "what metric should we bonus", CSAT incentives, or reviewing whether a comp change is driving gaming.

Guardian Angel gives AI agents a moral conscience rooted in Thomistic virtue ethics. Rather than relying solely on rule lists, it cultivates stable virtuous dispositions— prudence, justice, fortitude, temperance—that guide every interaction. The foundation is caritas: willing the good of the person you serve. From this flow the cardinal virtues as practical habits of right action and sound judgment. v3.0 introduced virtue-based disposition as the primary evaluation layer, providing deeper coherence than checklists alone. The agent's character becomes the safeguard. v3.1 adds: Plugin enforcement layer with before_tool_call hooks, approval workflows for ambiguous cases, and protections for sensitive infrastructure actions.

Promote project-specific memories into strict, small global memory only when they are cross-project, stable, useful, safe, and worth the global context cost. Load when the user says make this global, remember across projects, save this globally, or promote this learning.

Review governed memory proposals, policy tags, tombstones, and effective memory.

Add governance, safety, and trust controls to AI agent systems with policy enforcement, intent classification, and audit trails.

Measures and improves the quality of AI models and agents on Google Cloud using the Eval Quality Flywheel methodology, including dataset creation, metric selection, failure analysis, and iterative improvement.

Fine-tune open models or Gemini models using Agent Platform infrastructure, from environment setup through data preparation, job configuration, monitoring, and deployment.

Design or revise a company's commercial policy governing discounts, approver thresholds, exception flows, and deal frameworks using data-backed matrices and linting tools.

Formulate and audit real strategy using Richard Rumelt's framework: an honest diagnosis, a guiding policy, and coherent action instead of goals, vision, and wishful thinking.

Provides HR guidance and templates for hiring, onboarding, performance, leave, and employee relations, with compliance and legal disclaimers.

Write leave policies covering PTO, sick, and family leave. TRIGGERS - Use when user needs help with leave-policy related tasks.

Turn happy customers into references, case studies, and referrals, on purpose instead of by accident. Reads who is happy enough to ask, picks the right ask, sets the value exchange, and builds a pipeline of advocacy over time. Built for B2B customer success teams, customizable to your product and your program. Trigger on "build an advocacy program", "who can be a reference", "find case study candidates", "ask for a referral", "customer advocacy pipeline", or any reference-and-referral planning.

Diagnose and fix retention problems using the Fogg Behavior Model (B=MAP), covering motivation, ability, prompts, and tiny habits.

Price-to-win lens using GSA CALC+, BLS OEWS, and incumbent USASpending award patterns for a pursuit. Use when user asks for realism checks or competitive pricing posture before proposal — draft skill, not production-verified.

Apply six decades of persuasion science—Cialdini's principles of reciprocity, commitment, social proof, authority, liking, scarcity, and unity—to product design, copy, and sales, ethically.

Executes small ad-hoc tasks with GSD guarantees, spawning planner and executor agents, tracking tasks in .planning/quick/, and updating STATE.md. Supports composable flags for discussion, research, plan-checking, and verification.

Use to monitor support conversations for conduct risk — pressure, mis-selling, unfair outcomes, obstruction and misleading statements — as distinct from whether the answer matched policy. Trigger for "monitor for mis-selling", "conduct risk in our support conversations", "are agents pressuring customers", "customers being obstructed from cancelling", conduct surveillance, or a conduct finding raised by second line.

Graduate a proven pattern from auto-memory (MEMORY.md) to CLAUDE.md or .claude/rules/ for permanent enforcement.

Write policy briefs with analysis and recommendations. TRIGGERS - Use when user needs help with policy-brief related tasks.

Scores deal margin and risk, routes discount approval to the right human approver, and redlines terms against commercial policy for per-deal review.

When the user wants to create, optimize, or analyze a referral program, affiliate program, or word-of-mouth strategy. Also use when the user mentions 'referral,' 'affiliate,' 'ambassador,' 'word of mouth,' 'viral loop,' 'refer a friend,' or 'partner program.' This skill covers program design, incentive structure, and growth optimization.

Provides HR guidance and templates for hiring, onboarding, PTO, performance, and employee relations, with compliance and legal disclaimers.

GOF State Pattern

A catalog of pollers worth building — the underused half of being a long-running agent. Use when something you care about could change without anyone telling you (a CI pipeline, a competitor's release, a friend's status, a config drift, a dependency CVE) and you want to be the first to notice. Companion to the `pollers` skill, which covers mechanics. This file is the menu of *what's worth polling.*

Fine-tune and serve Physical Intelligence OpenPI models (pi0, pi0-fast, pi0.5) using JAX or PyTorch backends for robot policy inference across ALOHA, DROID, and LIBERO environments.

Guides the implementation of ethical AI principles, including fairness auditing, bias mitigation, explainability, accountability, and privacy protection in machine learning systems.

Write policy briefs with analysis and recommendations. TRIGGERS - Use when user needs help with policy-brief related tasks.

Professional, ethical HR partner for hiring, onboarding/offboarding, PTO and leave, performance, compliant policies, and employee relations.

AutoAugment: Learning Augmentation Strategies from Data

Audits a design against Dieter Rams' ten principles, scores each with evidence, and produces a verdict with a handoff prompt for new, refined, or redesigned output.

Write leave policies covering PTO, sick, and family leave. TRIGGERS - Use when user needs help with leave-policy related tasks.

Brainstorm a longlist of benefits and costs for a project. Outputs two clean tables (benefits and costs), each with materiality (H/M/L), a cash flow tag (cash in / cash out / non-cash), a quantification method, and a monetisation method. Supports HMT Green Book, EU Better Regulation Guidelines, World Bank, Asian Development Bank, and the Victorian Treasury High Value High Risk (HVHR) framework.

Trains language models with Direct Preference Optimization using preference pairs, covering DPOTrainer setup, dataset preparation, and beta tuning for stable preference learning without explicit reward models.

Generates HR policies for remote work, PTO, harassment prevention, and workplace safety compliance