engram
engram contains 8 collected skills from aiconnai, with repository-level occupation coverage and site-owned skill detail pages.
Skills in this repository
Use for an Engram dependency triage loop that watches advisories and lockfiles, proposes patch-only updates, rejects major upgrades without approval, and records reproducible verification commands.
Use for an Engram CI sweeper triage loop that groups CI failures, classifies root causes, caps attempts, and proposes bounded minimal-fix candidates only after budget, denylist, and verifier gates.
Use for an Engram daily triage loop that safely collects and classifies CI, issue, PR, commit, and chat signals into report-only handoff state with bounded scope, no auto-fix, and loop-run-log updates.
Use for an Engram PR babysitter triage loop that monitors PR aging, CI blocks, reviewer threads, and lightweight action proposals with isolated-worktree fix candidates and human escalation for risky changes.
Use when designing, implementing, auditing, hardening, or operating agent loops in this repository, including Claude Code/Grok Build/Codex style `/loop` workflows, explicit `/goal` runs, Git worktree orchestration, MCP and memory automation, sub-agent execution, STATE.md handoffs, cost controls, maker/checker verification, and the Engram security gate (full `sensors.sh` + AgentShield scan + `just ci`). Loops default to L1 report-only; autonomous execution against Engram requires a reviewed ADR per the harness security contract.
Weekly or manual security triage loop that executes AgentShield with a hard iteration cap and records the result in a repository state file.
Run structured consensus with Engram's `memory_council` tool and `CouncilSkill` SDK wrappers for architecture, design, policy, security, reliability, performance, ADR, or tradeoff decisions. Use when the user asks for consensus, council review, multi-agent-style review, decision rationale, option comparison, or mentions `llm-council`, `memory_council`, or `CouncilSkill`. Do not use for simple lookup, single-answer retrieval, or execution-only coding tasks after a decision is already made.
Bootstrap an AI agent's engram memory session in a new repository. Guides through loading prior context, project scan, workspace setup, first memory creation, search, and session close. Use when starting work in a repo that has engram configured, when setting up memory for the first time, or when a new agent needs to establish context. Skip if the session is already active and workspaces are already configured.