Results for “commit”

Orchestrate persistent agent memory across coding sessions, repos, and tools. Load when the user asks to remember, recall context, save project memory, create a handoff, manage global memory, update memory, compact memory, audit memory, forget memory, continue from prior sessions, or before commit/push/git operations that checkpoint project state.

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Set a deliberate visual direction before any UI is built — the single biggest lever against generic AI output. Derives a posture from product-soul/PRD/specs, scores a curated archetype palette, then generates 2-3 GENUINELY DISTINCT directions and compares them side-by-side before committing to one. Load when the user asks to pick an aesthetic, choose a design direction, decide what a UI should feel like, explore visual options, says "what should this look like", "make it feel like [Linear/Apple/ Duolingo]", "give me design directions", "explore some looks", or when frontend-design routes here. Replaces design-archetype. Sub-skill of frontend-design.

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Generate user-facing or internal release notes and changelogs. Load when the user prepares a release, tags a version, or wants to summarize recent progress. Also triggers on "write a changelog", "prepare release notes", "what's new in this version", "summarize my commits", or "create a release summary". Auto-triggered by library-skill after major repo changes (new skills added, skills renamed, structure changes). Applicable to any project, including this skill library itself.

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Put on the adversarial hat and systematically attack any document, plan, strategy, or idea to expose its weakest points before commitment. Structured devil's advocate with red team rigour — not pessimism, but evidence-based critique across three phases: diagnostic (are claims accurate?), creative (is the problem artificially constrained?), challenge (are solutions robust?). Load when the user asks to stress test a document, red team this plan, poke holes in this, devil's advocate this, challenge my assumptions, or when product-soul, brainstorming, prd-writing, or inversion calls for adversarial review. Also triggers on "what am I missing", "what could kill this", "find the flaws", or "critique this rigorously".

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Write a rigorous, decision-grade experiment spec — falsifiable hypothesis, primary metric, guardrails, randomisation unit, exposure definition, method (A/B, holdout, switchback, quasi-experiment, MAB), MDE/duration plan, peek policy, validity threats, and pre-committed decision rule. Platform-agnostic. Load when the user has a candidate experiment and needs to spec it before launch, or says "spec this experiment", "write the test plan", "design this A/B test", "what's the hypothesis", "how big a sample do we need", "how long should we run this", "define the metrics for this test", or when the experimentation orchestrator routes here.

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Sync the live ~/.claude global config (settings.json, CLAUDE.md, statusline.ts, own skills, skills.sh lock file) into this git backup repo, then commit. Allowlist-based so credentials, history, and project transcripts are never copied. Use when the user says "sync my claude config", "back up .claude", "update the .claude repo", or runs "/sync-claude".

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Verify a code change end-to-end in the current worktree: identify what changed, run the relevant tests, get the app running, drive a browser over the affected areas, and report a verdict with screenshots. Generic across project types (Laravel/Herd, Node/bun, frontend, CLI, library). Use when the user wants to verify/QA/smoke-test a change, check that a PR or branch works, validate uncommitted work, or says "/flow", "verify this change", "does this PR work", "test and click through this". Optional target: PR number/URL, branch/ref, or worktree path; default is the current working changes.

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Diagnose Sentry issues without copy-pasting stack traces. Uses the Composio CLI to pull issue details, events, breadcrumbs, and suspect commits, then maps the frames to local source so the agent can propose a fix directly.

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Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always

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Automated PR review and CI auto-fix for GitHub and GitLab using the Composio CLI. Pulls diffs, fetches failing job logs, posts review comments, and loops fix commits until checks go green.

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Use when a safety director, operations manager, or fleet owner asks for templates, topics, or structure for recurring safety meetings — weekly driver meetings, monthly safety committee meetings, quarterly all-hands safety reviews, or post-incident safety stand-downs.

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Use this skill when the user asks how to build, measure, or improve safety culture in a motor carrier — leading vs lagging safety indicators, blame-free reporting, near-miss programs, safety committee structure, monthly safety meetings, ATA Safety Management Program guidance, and how to evaluate cultural maturity. Reference ATA SMP + DOT safety culture research.

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Refute-before-prove research discipline: automated counterexample sweeps before any formalization, meter-integrity audits for information-bound experiments, mutation-tested model checkers, pre-registered commit-or-cut gates for speculative directions, wrong-turn reporting, and numeric-claim provenance. Use when validating any new theorem, bound, equilibrium, or security claim; when building or trusting a checker, simulator, or experiment; or when deciding whether a speculative research direction lives or dies. NOT for exploratory brainstorming, product prioritization, writing style, or literature review.

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Defensive counterpart to federated-harbor-redteam: closes the smells that red team opens against The Federated Harbor whitepaper. Federation-specific defenses for cross-harbor primitives — mechanization commitments, scope hedges, cross-paper dependency formalization, pre-emptive analogies (CT, Macaroons, atomic swaps), and defense-in-depth framing (refuses vs prices). Use during a versioned red-vs-white round; pairs with federated-harbor-redteam. NOT for ad-hoc code review, NOT for the Anchor or Bonded papers (use whitehat-defense).

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Apply GPGP/TAEMS coordination as local-scheduler constraints under explicit task, view, commitment, and delivery assumptions. NOT for assuming global task visibility, reliable delivery, or modern execution authority.

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Propose and safely admit immutable DAG revisions after failures, requirements, resource changes, or unresolved effects. NOT for mutating an executing graph in place or retrying an effect with unknown commit state.

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Apply Conway's homomorphism principle to multi-agent system design, recognizing that agent coordination structure predetermines system architecture and capability.

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Design an agent's handling of obligations, prohibitions, permissions, and conflicts among norms and goals. Use when an autonomous agent must decide which norms apply and what to do when they conflict. NOT for simple fixed policy checks, ordinary BDI commitment design, or organizational metaphor.

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Design an individual agent's belief, goal, intention, and reconsideration model. Use when specifying autonomous decision state, commitment policy, or recovery from failed plans. NOT for AgentSpeak interpreter mechanics, organization modeling, normative conflicts, or multi-agent execution waves.

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Author a pull request an AI coding agent can actually get merged: a scoped, coherent diff; a Summary and Test Plan backed by real evidence; correct triage of required-and-blocking CI gates versus external/advisory checks (e.g. a Cloudflare Pages preview build); draft-while-WIP discipline; named fixup commits for real review findings; and a clean landing through a merge queue without force-pushing or bypassing branch protection. Use when opening, updating, triaging red CI on, or landing an agent-authored GitHub PR. NOT for this repo's internal release ceremony, actor embodiments, or contributor mirror-sync mechanics (use port-daddy-internal-dev), tracking backlog/issue lifecycle across a board (use agent-issue-tracker-workflow), or deciding what to build next / sequencing a roadmap (use legible-roadmap-with-sidequests).

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Verify every visual-evidence artifact (screenshot/GIF/recording) attached to a PR carries a provenance manifest binding it to real daemon-backed truth — daemon port, run id, transcript head hash, agent node id, commit, and an honest real/fixture/mock source label — and that operator-control-panel PRs cover the required set of proof states. Use when gating a PR's proof artifacts before merge, auditing whether a "LIVE" visual claim is backed by a real daemon run versus a reused or fixture-backed mock, or defining the required state-coverage set for a control-panel change. NOT for the capture technique itself — headless Playwright, `screencapture -x -l`, non-interruptive capture (use port-daddy-agent-skill's visual-evidence doctrine), designing the receipt body schema an artifact attaches to (use agent-work-receipt-designer), or the broader dogfood/Potemkin product-quality bar (use multi-agent-authoring-product-bar).

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Design and audit a pricing function for variable-cost agent labor. Choose among per-seat, metered, credits, hybrid, and outcome pricing; name buyer value and cost metrics separately; calculate a reproducible cost floor; require pre-commitment guardrails; and stress-test declared personas. Use for offline pricing-design evidence, not billing implementation or runtime control. NOT for production billing, payment collection, or runtime spend enforcement.

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Discipline an AI agent needs to work an issue/task tracker (Jira, Linear, GitHub Issues) as the shared source of truth: pull the right next item instead of inventing work, search before creating to avoid duplicates, write actionable items with checkable acceptance criteria, keep status transitions honest, and link work to items via branches/PRs/commits so progress is legible. Use when an agent picks up tracker work, files a new issue, updates status, or closes an item. NOT for authoring the PR itself (use agent-pr-authoring), roadmap-level planning and prioritization (use legible-roadmap-with-sidequests), or the mechanics of multiple agents coordinating on the same codebase (use multi-agent-coordination).

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Run the full static analysis suite — ruff lint, ruff format check, pyright type check, auth analysis, license headers, example.env check. Use before committing or to verify code quality after changes.

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