AI Engineering
LLM integration, prompting, and agent engineering skills.
🧠
4w ago
H-Onboard
H-Onboard bootstraps Haft through one readable onboarding surface, prepares initial profile reviews or bounded scope relation changes, and orients specification carriers. Use for first-time setup, incomplete setup, or profile-underdetermined spec recovery.
AI Engineering
1.4K102
🧠
4w ago
H-Reason
H-Reason is a source-first umbrella for FPF-aware reasoning in a Haft project. Use when the operator asks to think through an ambiguous engineering, management, architecture, specification, or project question without naming a narrower Haft capability.
AI Engineering
1.4K102
🧠
4w ago
H-Reason
H-Reason provides source-first FPF-aware reasoning for ambiguous engineering, management, architecture, specification, or project questions in a Haft project. Use it when no narrower Haft capability is current; ordinary reasoning stays conversational and binding actions remain manual.
AI Engineering
1.4K102
📋
4w ago
H-Spec
H-Spec manages typed specification lifecycle and source-currentness repair: inspect current SpecSections, draft or clarify carriers, classify FPF semantic fanout, record operator-requested spec changes, and cross explicit approve/rebaseline/reopen gates only with human authorization. Use for spec status, updates, stale sections, newer source revisions, or semantic changes across carriers.
AI Engineering
1.4K102
📋
4w ago
H-Spec
H-Spec manages Haft's typed spec lifecycle, grounding drafts in repository evidence and current carriers, validating authored drafts, and repairing semantic fanout and L/A/D/E. Use it when authoring, tracing, or approving specs in Haft with explicit human gates.
AI Engineering
1.4K102
⚖️
4w ago
Haft Compare
Haft Compare compares two or more existing candidates under an explicit characteristic space, parity basis, and predeclared selection policy, returning constraints, trade-offs, and a non-dominated set rather than a single score. Use it when you need to evaluate options for an AI agent without scalarizing into one hidden ranking.
AI Engineering
1.4K102
🧭
4w ago
Haft Onboard
Haft Onboard bootstraps Haft through the readable task-level onboarding surface, prepares a non-binding project-profile review when needed, and orients only applicable typed spec carriers. Use it to keep profile apply and lifecycle gates human while setup is ready immediately after haft init.
AI Engineering
1.4K102
🧭
4w ago
Haft Status
Haft Status provides a read-only cockpit of a Haft project's active problems, decisions, notes, evidence freshness, drift, commissions, spec lifecycle, module coverage, and exact file-link gaps from the current code index. Use it for project status, session resumption, finding decision-linked items, or spotting what needs attention.
AI Engineering
1.4K102
🧠
4w ago
NoPUA
NoPUA drives AI with wisdom, trust, and inner motivation instead of fear and threats, activating when tasks fail repeatedly, loops occur, or frustration rises, to systematically penetrate obstacles and self-verify delivery.
AI Engineering
1.4K48
🧘
4w ago
NoPUA
NoPUA guides AI agents to persist through repeated task failures and avoid passive behavior by replacing pressure with wisdom, trust, and inner motivation. It activates after two or more failures, when the agent suggests manual work, blames unverified environments, loops, or shows low initiative.
AI Engineering
1.4K48
🌊
4w ago
NoPUA
NoPUA helps AI agents recover from repeated failures and stuck loops by applying Taoist-inspired wisdom, systematic debugging, and proactive ownership instead of fear-based pressure. It activates when an agent is about to give up, suggests manual work, or gets stuck after multiple attempts.
AI Engineering
1.4K48
🧠
4w ago
NoPUA
NoPUA drives AI agents to persist through repeated failures with wisdom, trust, and inner motivation instead of fear. Use it when an agent gets stuck, loops, asks the user to do manual work, or gives up too early.
AI Engineering
1.4K48