「firm」の検索結果

Prepares the contents of a dated backup of a custom skills folder and drafts a session journal entry, both for the user to save, so work can be resumed after a crash, a context loss or a skills wipe. Returns the copy action list, backup manifest, journal entry, resume summary and a restore plan whose steps the user confirms one by one and carries out. Use when the user asks to "back up my skills folder", "checkpoint this session", "write the session journal", "where did we leave off last time", "restore my skills from the last backup" or "take a safety copy before I edit this skill". Do not use for holding individual file changes for approval during ordinary work, use no-delete-guardrail instead. Drafts for human review; never approves, authorises or signs off.

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。

Reviews a set of knowledge files or a knowledge base listing and returns a draft hygiene table, one row per file: duplication signals with the matching file, staleness signals, conflicts between files on the same topic with both passages quoted, missing or unverified owners, and one proposed action per file (Keep, Update, Merge into, Retire, Assign owner, Confirm with owner) for the owner to decide. Never edits, merges, moves or deletes a file. Use when the user asks to "review our knowledge base for duplicates", "which KB articles are stale", "find conflicting articles", "which articles have no owner" or "run a hygiene check on these files". Do not use for review-date sweeps of a document library with owner reminders, use sharepoint-review-sweeper instead; for writing one article, use knowledge-article-drafter. Drafts for human review; never approves, authorises or signs off.

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。

Drafts one issue of an internal newsletter from the items the user provides (notes, messages, snippets, meeting outputs, contributor submissions): a running order with the reason for each position, a factual headline and one paragraph per item with its source line, one call to action per item with date and route, two subject-line options, an item register accounting for every item supplied, and a list of items that need an owner's confirmation before send. Use when the user asks to "draft this month's newsletter", "turn these items into the team update", "write the staff bulletin from these notes", "order and headline these items" or "prepare the internal digest". Do not use for one piece of news that needs its own send, use announcement-drafter instead; for a digest of external news, use news-monitor-digest; for a personal weekly status note, use weekly-status-update-writer. Drafts for human review; never approves, authorises or signs off.

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。

Turns an access export (accounts, entitlements, grant and last-used dates per system) into a draft access review pack, one section per system owner: who has what, since when, anomalies to confirm and the decision each line needs, with a blank column for the owner's decision. Never decides, revokes or rates access. Use when the user asks to "prepare the access review pack", "split this entitlement export by system owner", "who has access to what in this system", "build the recertification pack from this export" or "draft the access attestation for the owners". Do not use for a single request for a tool or access, use software-request-review instead. Drafts for human review; never approves, authorises or signs off.

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。

Organize user-scoped CLEC episodes into traceable Traditional Chinese Obsidian pages. Use when Codex must group X, pCloud, Google Drive, Bilibili, Odysee, and RSS or Podcast sources by five-digit episode number; obtain and review transcripts through media-transcript; clean readable transcripts with the confirmed CLEC lexicon; anonymize students; or build the standard three-layer episode page.

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。

Bring past diagnoses to a bug before fixing it, record the new root-cause hypothesis, and close it as confirmed or refuted once the fix is verified. Use when a bug could come from more than one layer, or looks like something seen before.

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。

Prepare and launch LoRA, LoKr, or T-LoRA training through lora-scripts-next (SD-Trainer), Anima-first. Use when the user asks to train a character, style, or concept LoRA, choose parameters or repeats and epochs, start a run, or monitor training on Anima, SD1.5, SDXL, or Flux. Organize and caption the dataset, run dataset-doctor, choose a documented starting preset from image count and VRAM, show one confirmation card, then call the mikazuki API and monitor its log.

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。

Audit and repair a kohya-style LoRA dataset before training. Use when the user asks to check, validate, inspect, fix, clean, 体检, or 修 a dataset, captions, or tags. Inspect image count, repeats and step budget, resolution and aspect buckets, duplicates, corrupt or non-RGB images, missing or empty captions, trigger consistency, and tag-frequency hygiene. Return a structural PASS, WARN, or FAIL report and apply only confirmed fix_dataset.py actions, dry-run first with displaced originals quarantined.

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。

Modern C++ project setup: CMake/CMakePresets, vcpkg, Ninja, VS Code/clangd, GoogleTest, clang-format/tidy, Doxygen, CI, macOS/Linux/Windows. Use for bootstrapping or modernizing host-side C++ apps and libraries; prefer embedded-project-setup for MCU firmware and cross-debug flows.

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。

- End-to-end workflow to establish where and when a photo or video was captured and whether it is authentic — evidentiary handling, metadata extraction, reverse image search for provenance, visual geolocation, chronolocation from shadows, and manipulation… Use when asked to verify where an image was taken, confirm or refute a claimed location or date, or authenticate media before relying on it

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。

- Enumerate a username across hundreds of platforms with sherlock, maigret and WhatsMyName, then correlate and confirm which accounts genuinely belong to the same person.

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。

Introduce two or more people from the owner's network: resolve and confirm both identities, DM each side for consent before any group exists, then create the group and introduce both sides inside it. Requires the owner's approval first. Triggers: "/intro", "introduce X and Y", "connect X with Y".

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。

Publish an already-vetted post to a personal Facebook wall through the owner's real logged-in Chrome tab (a low-ban-risk path), rate-limit-guarded and draft-first: paste, verify what is actually in the composer, confirm after reload. Triggers: "/fb-post", "publish to facebook", "post this to my wall".

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。

Set up APIClaw and land one live API execute. When a user says "set up https://apiclaw.cloud/SKILL.md", or you need a research API call without collecting provider keys, follow this file. Auth is Clerk via `npx @nordsym/apiclaw auth login`. Confirm with `npx @nordsym/apiclaw auth whoami` before any execute. Execution is POST /v1/execute with provider/action. Never ask the user to paste a token into chat. Never pass a catalog display name to `apiclaw call`.

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。

Autonomous AI security pen testing. Executes real exploits against web applications to find SQL injection, XSS, SSRF, authentication flaws, and IDOR vulnerabilities. Reports only confirmed, reproducible findings — no false positives.

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。

Senior embedded software engineer specializing in firmware and driver development for ARM Cortex-M microcontrollers (Teensy, STM32, nRF52, SAMD).

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。

Use when the user asks to "script this short video", "write a TikTok / Reels / Shorts script", "给这条抖音或视频号视频写脚本", or "fix the hook — viewers drop off in the first seconds"; produces timestamped beat-sheet scripts on the retention-gate model (0-2s hook / 2-5s confirmation / 5-15s payoff / loop-or-CTA) with per-scene script lines, on-screen text for muted viewing, asset keywords, and 9:16 format-param rows per platform norm card for TikTok, Reels, Shorts, 抖音, and 视频号 — plus 2-3 hook options from named hook families and an AI-content disclosure line by default on realistic synthetic media. Spec-only: rendering, TTS, and publishing stay with the user's own tools — no pipelines, no upload automation. Not for creator video briefs — use brief-generator; long-form video SEO belongs to content-writer. 短视频脚本/抖音分镜/开头钩子/竖屏9:16

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。

Use when the user asks to "build a win-back campaign", "re-engage lapsed subscribers", "run a re-permission / re-consent sweep", or "sunset my dead list"; produces a closed-loop reactivation program — a lapsed-cohort definition, a staged offer ladder, a re-consent (re-permission) capture step, and a sunset-confirm / suppression rule. Owns none of the SEND-N sub-item notes: engagement-decay / sunset is email-sequence-designer's and preference-center / frequency options is preference-frequency-manager's — this skill references those notes, it does not re-emit them. Not for the general lifecycle flows (welcome/cart/post-purchase) — use email-sequence-designer; not for the preference-center / opt-down ladder — use preference-frequency-manager; not for the consent record itself — use consent-registry; not for computing EQS or the N1 veto — use email-quality-auditor. 流失召回/重新授权/沉默用户清理

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。

Use when the user asks to "grow my email list", "design a lead magnet / signup incentive", "set up double opt-in", or "plan a referral / recommendation loop"; produces a list-growth plan — acquisition channels, lead-magnet / incentive concepts, a compliant double-opt-in capture-flow spec, referral-loop mechanics, and subscriber-growth / cost-per-opt-in targets (labeled Estimated) — that feeds SEND-S (consent quality captured at acquisition) and SEND-N (lifecycle entry). Not for the signup page/popup UX itself — use landing-optimizer; not for recording the opt-in — use consent-registry; not for the confirmation-email copy — use email-creative-builder. 邮件列表增长/lead magnet/双重确认/推荐环

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。

Bluetooth context for the Megahub project. Use when working on BLE GATT server, Classic Bluetooth HID host, Web Bluetooth API integration, btremote library, connection handling, or any Bluetooth-related firmware code.

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。

Apply when tempted to ask 'should I do X?' on reversible work. Proceed, present the result, let the human course-correct after the fact; reserve confirmation for irreversible actions.

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。

Create an Estuary derivation that flattens a nested array into one output document per array element. Use for normalising nested JSON, exploding line items, unpacking tags, or producing one-row-per-item tables from arrays. Derivations add complexity and cost — confirm the user wants a derivation before reaching for this (some destinations can `UNNEST` server-side without one). Use when user says "flatten-array derivation", "derivation to explode an array", "transformation to unnest", "derive one row per item", or "flatten nested data with a derivation".

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。

Write Estuary derivations in Python — async-generator transforms, Pydantic-typed source/output, optional persistent state, and dependency installation via uv. Use for ML/embeddings, async API calls, or any transform where SQL and TypeScript are awkward. Derivations add complexity and cost (and Python derivations require a private/BYOC data plane) — confirm the user wants a Python derivation before reaching for this. Use when user says "python derivation", "write a derivation in python", "embed with a python derivation", "ML derivation", "call an API from a derivation", or anything mentioning model2vec / huggingface / pydantic in a derivation context.

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。

Create an Estuary derivation that continuously aggregates metrics (daily totals, running counts, min/max, lifetime revenue) using reduction annotations. Use for real-time dashboards, continuous materialised views, and replacing batch ETL aggregations with streaming. Derivations add complexity and cost — confirm the user wants a derivation before reaching for this. Use when user says "aggregation derivation", "derivation to sum daily totals", "running-count derivation", "transformation for min/max per group", "derive lifetime metrics", "aggregate-by-date derivation", or "real-time-dashboard derivation".

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。