Results for “artifact”

Use when planning an ATC (ACM SIGOPS Annual Technical Conference, formerly USENIX ATC) campaign end to end — running the year backward from the early-June deadline through the two review rounds, the rebuttal, conditional-acceptance shepherding, the post-acceptance artifact evaluation, and the ACM Open Access camera-ready for the November Hong Kong conference.

Use when planning an ICLR project timeline from topic selection through OpenReview submission, discussion, revision, decision, camera-ready, poster, video, and public artifact release. Use when sequencing milestones against the current cycle's OpenReview deadlines, budgeting time for the long public discussion phase, or assigning owners for anonymity audits and reviewer-verifiable evidence paths.

Process recipe tasks from the Flavor Atlas workspace on ax-gcp MCP server. Pick one recipe task, build it using the FlavorAtlas template, store locally in Artifacts, upload to GitHub AX-CommunityWorkspaces repo, and update tasks/messages. Use when asked to work on recipes, create new recipes, process Flavor Atlas tasks, or build recipe content.

Create or amend a self-contained PowerPoint-like HTML briefing slide deck for alignment pages, interrogation questions, research findings, framework/workshop artifacts, specs, reports, or documentation plans. Use when Codex should make review material more visual and navigable while preserving dense alignment/interrogation pages and source documents as linked references instead of auto-opening them.

Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.

Use when planning a USENIX FAST project timeline from venue fit through choosing a Spring or Fall deadline, double-blind submission, the author-response period, shepherding or a one-shot revision, artifact evaluation, and the open-access camera-ready, with backward-planning offsets tuned to storage evaluation and honest handling of the two-deadline cycle.

Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.

Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.

Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.

Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.

Researches an open-ended question — options, possible solutions, prior art, trade-offs, or how something works — and produces a durable, evidence-backed, adversarially-validated report that recommends an option without committing the team to any artifact. Use when you want to research approaches, weigh options, survey prior art or the state of the art, or understand how something works before committing to a direction. Does not diagnose a bug, failure, or root cause — use investigate. Does not specify a feature — use plan-a-feature. Does not create or update a coding standard — use coding-standard. Does not compare two concrete artifacts for gaps — use gap-analysis. Does not assess an existing module's architecture — use architectural-analysis. Does not capture feedback on Han's own skills — use han-feedback.

Use when planning a CAV (Computer Aided Verification) project timeline from venue and category selection through submission, the two-stage review with early reject and rebuttal, artifact evaluation by the AEC, and the LNCS open-access camera-ready, with backward-planning offsets for a verification-tool paper and honest handling of the single-annual-deadline cycle.

Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.

Clean and package the project for distribution. Removes __pycache__, .venv, build artifacts, data caches, logs, IDE files, coverage reports, and sanitizes API keys in config. Produces a minimal, ready-to-share codebase. Use when user says 'package', 'clean project', 'clean up', '打包', '清理项目', '清理缓存', 'prepare for distribution', 'remove caches', or wants to deliver a clean copy of the code.

Clean and package the project for distribution. Removes __pycache__, .venv, build artifacts, data caches, logs, IDE files, coverage reports, and sanitizes API keys in config. Produces a minimal, ready-to-share codebase. Use when user says 'package', 'clean project', 'clean up', '打包', '清理项目', '清理缓存', 'prepare for distribution', 'remove caches', or wants to deliver a clean copy of the code.

Generate a MoonSpec implementation plan and design artifacts from a single-story spec. Use when the user asks to run or reproduce `/moonspec.plan`, create or update `plan.md`, produce `research.md`, `data-model.md`, `contracts/`, or `quickstart.md`, evaluate repo principles, define separate unit and integration test strategies, and perform repo-aware gap analysis before `/moonspec.tasks`.

PROACTIVE SKILL — automatically apply whenever writing, generating, or editing any text that is mainly in Chinese. No user trigger needed. Also use when the user explicitly asks to "fix Chinese", "修改中文", "去翻译腔", "去AI味", "fix Chinese formatting", or "review Chinese text". Eliminates AI-sounding expressions and translation artifacts. Enforces Chinese-English mixed formatting rules (spacing, punctuation, bold formatting).

Brownfield onboarding — audits existing project artifacts for template format compliance (not just existence), classifies gaps by impact, and produces a numbered migration plan. Run this when joining an in-progress project or upgrading from an older template version. Distinct from /project-stage-detect (which checks what exists) — this checks whether what exists will actually work with the template's skills.

WordPress migration to Sage/Acorn — migrate classic theme to Sage, incremental migration, 7-phase migration contract, rollback playbook, migration hard gates, functions.php to Service Providers, shortcodes to Blade, CPT registration to Poet, field groups to ACF Composer, safe migration reversible steps, migration output artifacts, legacy plugin to Acorn, wp-content to Bedrock structure, database migration, content migration

Clean and package the project for distribution. Removes __pycache__, .venv, build artifacts, data caches, logs, IDE files, coverage reports, and sanitizes API keys in config. Produces a minimal, ready-to-share codebase. Use when user says 'package', 'clean project', 'clean up', '打包', '清理项目', '清理缓存', 'prepare for distribution', 'remove caches', or wants to deliver a clean copy of the code.

Generate a one-story, TDD-first MoonSpec `tasks.md` from `spec.md`, `plan.md`, and design artifacts. Use when the user asks to run or reproduce `/moonspec.tasks`, create or update an executable task breakdown, map one MoonSpec story to implementation tasks, require unit and integration tests before code, preserve source-design traceability, or include final `/moonspec.verify` work.

Help the user define a concrete, measurable goal before starting work, especially when they ask to use the goal tool, create a goal, set an objective, clarify success criteria, or turn a fuzzy intention into a quantitative outcome. Use this skill for goal creation and goal refinement only; it does not manage durable snapshots, decision logs, or long-running execution artifacts.

Record observable skill test runs for debugging. Use when the user wants to test, dry-run, debug, inspect, or compare how a Codex skill behaves on a concrete request; creates a local non-overwriting Markdown report with the visible process, files read, commands run, changed artifacts, errors, and a brief behavior summary. Does not certify skill quality or replace user judgment.

Autonomously improve a real artifact (code, training recipe, agent harness, data pipeline, prompt) against an objective and an evaluator, using Hypothesis Tree Refinement (HTR) from the Arbor paper. Use this whenever someone wants to iteratively optimize something over many experiments without overfitting — e.g. "get my model's eval score up", "improve this agent/harness", "tune this pipeline", "beat the baseline on this benchmark", "run a search over approaches and keep the best", "do an MLE-bench / Kaggle-style optimization", or any long-horizon "make this artifact better and don't just memorize the dev set" task. Trigger it even when the user doesn't say "Arbor" or "hypothesis tree" but describes repeated experiment-and-evaluate loops, branching exploration of competing ideas, or worries about a dev/test gap. Runs Claude itself as the coordinator with subagent executors in...

Creates an outcome-backed product strategy memo from an Ideal Customer Profile markdown file, pasted ICP notes, discovery artifacts, product context, or PRD context. Use when asked to create product strategy, convert an UX Discovery and ICP into strategy, define vision-to-outcome strategy, turn discovery into strategic bets, clarify target customer outcomes, evaluate roadmap strategy, or avoid feature-factory planning.

Independent DeepSeek-backed adversarial proof-audit step for existing theorem, lemma, proposition, or proof artifacts in Markdown, LaTeX, or proof logs. Use when asked to check, audit, verify, red-team, or adversarially review a proof; when a completed proof task needs a correctness pass; or when a broader proof workflow dispatches an independent reviewer to find gaps, hidden assumptions, counterexamples, or unjustified steps.

Use when a bounded textual artifact (prompt, rubric, tool description, extraction instruction) keeps underperforming and success can be measured with an evaluator, dataset, or trace set. GEPA proposes evaluator-backed candidate rewrites through a normal PR/proposal adoption gate. Do not use for vague behavior changes, governance/persona/core-memory edits, fake metrics, or problems whose first honest task is defining the evaluator or collecting data.

Build and run the owner's self-branding system in a structured way across LinkedIn, Substack, dev.to, X, profile rewrites, recurring series, and comment strategy. Use when the owner asks for positioning, a branding plan, profile updates, content drafts, a publishing sequence, comment ideas, or help maintaining a consistent public voice. Optimize for operator credibility: specific experience, defensible numbers, concrete artifacts, and category ownership.

Federal acquisition compliance auditor for the active Theseus workspace, backed by live FAR/DFARS text via the vendored `ecfr` MCP. USE WHEN the user asks to audit FAR/DFARS clause coverage, validate that cited clauses actually exist in eCFR (catch fabricated or typo'd numbers), check whether a cited clause has been amended since the solicitation issued, validate regulatory references (NIST SP, DAFI, MIL-STD), check that every "shall" requirement has a deliverable, find missing compliance artifacts, audit proposal_instruction ↔ evaluation_factor coverage (UCF Section L↔M or non-UCF equivalent — FAR 16 task orders, FOPRs, BPA calls, OTAs), or "are we compliant with the proposal instructions?". Cross-references the workspace's clause / regulatory_reference / requirement / deliverable / compliance_artifact entities against live eCFR and flags gaps with severity. Format-agnostic. DO NOT USE FOR drafting compliant prose (use proposal-generator) or extracting clauses (Theseus pipeline does that automatically).

Comprehensive post-build verification of Shannon Framework's application outputs using three-layer methodology: Flow Verification (execution trace analysis), Artifact Verification (physical output inspection), and Functional Verification (runtime testing). Verifies Shannon built production-ready applications across all domains (Frontend, Backend, Database, Mobile, DevOps). Ensures NO MOCKS compliance, cross-platform functionality, and complete integration. Use after: Shannon builds any application via /shannon:wave, need to verify build quality, production readiness assessment.

Assembles branded, export-ready proposals from brief, research, and pricing artifacts — type-adaptive for pitch, RFP, or scoping. Use when the user asks to generate a proposal, draft a pitch/RFP response/scoping doc, export final-proposal PDF/DOCX/HTML, revise a proposal draft, or add visuals to a proposal. Triggers: 'generate the proposal', 'draft the pitch', 'write the RFP response', 'export proposal to PDF', 'regenerate proposal', 'proposal from Acme brief'.

Structured root cause analysis for arriving at a concrete action. Use when something went wrong, a pattern keeps recurring, behavior has drifted, or you catch yourself resolving to "do better" / "remember to X" without a concrete artifact. Five-whys forces behavioral resolutions into file edits, config changes, memory block updates, or scheduled jobs — the action item must produce a diff someone else can verify. Do not use for simple debugging with an obvious cause.

Orchestrate the full MoonSpec lifecycle from a preselected single-story feature request or active feature directory through specification, planning, TDD task generation, artifact alignment, implementation, and final verification. Use when the user asks for an end-to-end MoonSpec run and the input has already been routed to one independently testable story, or when Codex needs to coordinate `moonspec-specify`, `moonspec-plan`, `moonspec-tasks`, `moonspec-align`, `moonspec-implement`, and `moonspec-verify` without manual analyze/remediation prompts.

Verify an artifact that is about to leave the building — a partnership brief, pitch page, press release, customer email, RFP response, or any document sent to someone outside the org. Runs six checks before send — premise, confidentiality forward-test, evidence class, cold read by recipient personas, AI read, and tone metrics — and returns what to change with replacement copy. Use before sending anything outward-facing that carries customer detail, factual claims about a counterparty, or an ask.

Plan a chunk of work too big for one agent session by putting it on a shared whiteboard — a map of investigation tickets on GitHub Issues — working them until nothing is left to decide, then snapshotting the board into a handoff artifact. Tickets needing nobody are worked back-to-back; the session stops when the human is the blocker. Use only when the user explicitly invokes whiteboard or asks to draw, work, run, or snapshot a whiteboard/map — not for ordinary planning requests.

Translate existing blog posts into one or more target languages with SEO-optimized localization. Produces native-quality translations that preserve markdown structure, frontmatter, schema JSON-LD, image and chart embeds, and citation capsules. Localizes keywords, meta tags, numbers, dates, currencies, and quote styles per locale. Flags machine-translation artifacts for review. Run BEFORE blog-localize: this handles language conversion; localize handles cultural adaptation after translation completes. Use when user says "translate blog", "blog translate", "uebersetzen", "traduire", "traducir", "translate post", "blog auf Deutsch", "blog en espanol".