「revision」の検索結果

Review and adapt MetaX attention backends, MLA, sparse indexers, cache layouts, and their kernel wrappers against a target vLLM revision and the actually installed MetaX component APIs. Verify dispatch, supported configurations, and GPU numerical behavior. Use for attention adaptations outside vllm_metax/patch/; do not apply monkey-patch headers or patch audit requirements.

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Disciplined, validation-gated revision of an EXISTING skill so each edit is a measured improvement rather than a guess. Use when editing, revising, or tuning a skill that already exists and there is evidence it underperforms (observed failures, drift, complaints) — invoke by name, or have versioning-skills / creating-skill defer to it before applying edits. Not for authoring a brand-new skill from scratch (use creating-skill) or one-off prose.

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Use when a screen design needs variants - how many, one document per variant, what makes two variants genuinely different, recommending one, how the human's choice is read, and narrowing to the chosen one in revision

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Use when a task in code_review was sent back before (an earlier need_revision comment exists) - verify every prior point was fixed at its root

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Use when any case fails or you reject a criterion - what goes in the review_criterion note, the failed case and the numbered need_revision comment, with severity

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Use when a task is in pm_uat - verify every acceptance criterion and the human's comments yourself in the browser, on a device, or over a loopback HTTP request, record a verdict per criterion, then move to human_uat or need_revision

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Master workflow for an implementation task. Use when you pick up any task or bug that changes product code, including a need_revision bounce.

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How to work a task returned with review, QA or UAT findings. Use when a task is in need_revision or PR review comments are in your context.

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Root-cause debugging discipline. Use when a test, build or pipeline fails, behaviour does not match expectations, a bug task arrives, or a task comes back in need_revision — before proposing any fix.

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Convert PDF files into editable Word documents with ComPDF. Use for PDF-to-Word requests involving contracts, reports, forms, proposals, review, revision, localization, or business reuse.

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Prove a deploy landed — the served revision is the commit you meant, its env is present, and the product does its job — instead of trusting the deploy command's exit code. Also catches server drift before a pull or deploy. Use after any deploy, rollout, restart or server-side fix ("задеплой", "выкати", "проверь на проде", "почему не обновилось"). Loaded by devops, l3-support, infra-provisioner.

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Design a spaced retrieval schedule for any topic list and timeline. Use when planning units, term sequences, or revision programmes.

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Generate retrieval practice questions at varied difficulty levels for a topic or concept. Use when creating quiz starters, revision activities, or low-stakes testing materials.

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Redesign a blocked topic sequence into an interleaved plan with mixed practice across related topics. Use when planning units, homework schedules, or revision programmes.

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Naming and classifying organisms through binomial nomenclature, the Linnaean hierarchy, type specimens, and the rules governing taxonomic authority and revision. Covers the structure of a scientific name, the ranks from domain to subspecies, the codes (ICZN, ICN, ICNP), and the modern phylogenetic refinements that reshape the classical system. Use when the task is to place a known organism in its formal hierarchy or to reason about how names change over time.

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Custom board bringup for Zephyr RTOS using Hardware Model v2 (HWMv2). Covers directory structure, board.yml metadata, core configuration files (Kconfig, defconfig, CMake), and revision management. Trigger when creating new board definitions or porting Zephyr to custom hardware.

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Manages the research/ knowledge base of verified tool and library research entries via knowledge-explorer.py. Commands — list (browse by category or SDLC layer), fetch-github (draft entry from GitHub repo), add (validate and route to category dir), update-append (append dated revision), generate-descriptions (repair missing or low-quality descriptions), migrate (convert inline-header entries to frontmatter). Use when browsing KB topics, adding or updating research entries, fetching GitHub repo metadata, generating descriptions in parallel via Haiku subagents, or migrating old-format entries to skill-spec frontmatter.

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Modern Git workflows, best practices, and commands. Use when the user asks about Git branch management (git switch vs checkout), file restoration (git restore), fixup commits, autosquash rebasing, git worktrees, rerere, force-with-lease, repository cleanup (git clean, stale branches, bloat analysis), history navigation (revision syntax, range notation, pickaxe search), recommended global git config, or GitButler and the but CLI.

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Use this skill when a human needs to review a Deepline Play result and hand feedback, labels, or approval back to the agent for revision, evaluation, comparison, or bounded iteration. Triggers on “put this run in a Sheet,” “review these results,” “read my feedback,” “make this a standing rule,” “never regress on this case,” “compare these runs,” “keep improving,” or “add the revised run to the same spreadsheet.” Skip ordinary Play authoring or execution with no human review loop, generic spreadsheet work, and one-off CSV export.

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Reviews a whole deliverable (talk, course module, paper, chapter, or referee report) against its manifest without rewriting it. Runs a deterministic gate for build, citations, numbers, facts, and leaks and stops on failure, then runs a finder over each section and a strong-model pass over the whole work, and adjudicates into checks/<date>/findings.json and report.md with anchored findings, severities, and honest NOT CHECKED coverage within a dollar budget. Use when asked to lint or review the whole talk, module, or paper, for a pre-ship review, or for the night shift. Revision stays serial and author-led.

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Drafts a referee report for a journal editor. Produces a recommendation, claim-and-design summary, three to six decision-driving concerns, additional concerns, and a revision plan through five parallel adversarial finders, Breaker, Butcher, Shredder, Void, Situator, a Blue Team error filter, Chief Reviewer synthesis, Tone Guard legal pass, and optional confidential editor note. Use when the user has been asked to referee a manuscript. Self-audits go to paper-review-lite or presubmit, and author responses go to referee-response.

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Organize an author's response to peer review: extract every referee point, order the revision by dependency, flag possible pushbacks, and build the response-letter skeleton the author fills in. Use for revise-and-resubmit planning, response letters, or checking every point was answered.

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Measure whether a change made the stack simpler, on numbers rather than impressions — line counts, branching, coupling, interface width, rule count and model-visible prose — and compare revisions or a whole PR stack on all of them at once. Use before claiming a pass reduced complexity, and when deciding which of several PRs added the machinery.

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Builds, revises, restyles, and critiques deliberate, editable Feishu / Lark whiteboards from content, references, existing SVGs, or live boards. Use for whiteboards, infographics, diagrams, system maps, timelines, decision boards, posters, and visual explainers that need factual fidelity, strong hierarchy, intentional composition, and evidence-based review rather than a generic grid of equal cards. Routes creation, revision, and critique through separate playbooks; commits to a content-and-design contract before drawing; validates deterministic SVG defects; renders and inspects the actual artifact; and uses an independent final reviewer for material deliveries.

日本語の概要は準備中です。原文の説明を表示しています。