「the」の検索結果

Fetches the most recent usable LinkedIn post from a company page OR a person's profile and stores the post content itself, with an optional AI personalization line on top. Triggers on "what did they post about", "recent LinkedIn post", "social signal", "reference their content", "they posted about X", "what is this person posting", "engage with their content". Outputs social_post_text (the raw post) plus social_post_url and social_post_days_ago; social_post_line only when the operator asks for one.

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。

Point at something on the human's macOS screen with a big arrow and a sign ("Franz, click HERE") using the bigarrow CLI. Use whenever the human has to look at, click, type into or choose a specific spot, button, field, window, tab or menu: show me where, point to it, which button, where do I click, zeig mir wo, guide me through this UI, the human must approve or sign something, or you need the human's hand and they may not be looking at the terminal. Mandatory when it is time-critical: a code that expires, a login or payment page that times out, a build waiting on the human.

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。

Step 4 of the PaperOrchestra pipeline (arXiv:2604.05018). ONE single multimodal LLM call that drafts the remaining paper sections (Abstract, Methodology, Experiments, Conclusion), extracts numeric values from experimental_log.md into LaTeX booktabs tables, splices the generated figures from Step 2, and merges everything into the template that already contains Intro + Related Work from Step 3. TRIGGER when the orchestrator delegates Step 4 or when the user asks to "write the methodology and experiments sections" or "fill in the rest of the paper".

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。

Step 3 of the PaperOrchestra pipeline (arXiv:2604.05018). Execute the literature search strategy from outline.json — discover candidate papers via web search, verify them through Semantic Scholar (Levenshtein > 70 fuzzy title match, temporal cutoff, dedup by paperId), cross-corroborate against Crossref + OpenAlex to flag hallucinated citations, build a BibTeX file, and draft Introduction + Related Work using ≥90% of the verified pool. Runs in parallel with the plotting-agent. TRIGGER when the orchestrator delegates Step 3 or when the user asks to "find citations for my paper", "draft the related work", or "build the bibliography".

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。

Monthly, on the last weekday. Re-tests every segment in strategy/icp.md against the evidence in this kit's own ledgers, then rewrites the targeting itself where the evidence disagrees with the assumption the segment was written on. It records every change in strategy/CHANGELOG.md. It sends only where you released the channel, never re-queues anyone, never edits the contacted ledger, and never writes a number it did not read out of a named file.

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。

Weekdays, file work only, no browser at all. Takes the single highest ranked open fault on the fleet and turns it into something the member can act on in a minute: the fault in one sentence, the first record that shows it, what changed around that date, three ranked causes each with its evidence line, what the failure has cost, and one paste ready correction line with the exact path it belongs in. It reads other Employees strictly read only, writes nothing outside its own folder, sends only where you released the channel, spends only where you released it, and never touches a credential.

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。

Weekly, browser only when a source refuses to be fetched. Counts unpublished calendar entries per property by folding the published ledger against the calendar, and where every property is above its runway threshold it records the counts and exits, which is the normal run. Where a property is low it researches the next block from rank evidence, the topic map, and live result sets, refuses any keyword already targeted, and appends fully specified entries after the last existing block. It is the only writer of the calendar and it never modifies, reorders, or renumbers an existing entry.

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。

Weekly, conditional browser lane, read only everywhere. Scores the fleet and the business for the week with a source beside every single number and no number anywhere without one, cites the Employee that owns a metric rather than recomputing it, refuses a rate below the floor, and writes one capped weekly page. It opens a browser only where the metric map names a live screen, never writes into another Employee's folder, sends only where you released the channel, spends only where you released it, and never touches a credential.

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。

Weekdays, browser only when the card needs one. Takes the next ready cards off the launch board and does the work each one names: stages copy into the dashboard, fills a directory or press form and leaves it open in its tab, verifies a setup, packages a handoff, or researches its own next targets. It ticks its own card the moment it has verified the file that closes it. It submits only where you released the channel, sends only where you released the channel, spends only where you released it, and never touches a credential.

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。

Weekly on a Friday, conditional browser lane. Scores the week from the ledgers with a source beside every number and an estimate nowhere, reads the review and rating movement off the member's own listing screens, replays the browser flows the weekday routines depend on, and names the one product change that would have removed the most tickets this week. It sends only where you released the channel, never posts, never resolves anything, spends only where you released it, and never touches a credential.

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。

Weekdays, heavy browser lane. Reads the member's own saved searches and the named sources for one buyer segment, captures candidate accounts together with the contactable people attached to them, scores every row against the named tests in the qualification file, and writes each one with the evidence that qualified it. Read only on every people surface, LinkedIn included. It holds every outbound action unless you released the channel, and it never touches a credential.

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 needs to understand competitors — direct, indirect, and substitute tiers, positioning map, SWOT, ad and content benchmark, pricing comparison, and the market gap to attack, using SimilarWeb, Ahrefs, Semrush, and the Meta Ad Library. Trigger on 'competitor research', 'competitive analysis', 'what are competitors running', 'who else sells this', 'why do people pick them over us', 'benchmark us against the market'. Also use when the user sends a competitor link and asks for an opinion. Not for — understanding the customer rather than the rival, see `09-customer-insight-global`; turning difference into a statement, see `58-positioning-global`; paid targeting, see `51-audience-research-global`.

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。

Decision rubric for promoting a prose prompt into a typed DSPy Signature. This is an ENHANCE overlay on top of the [[dspy]] library skill: it does NOT teach DSPy syntax — it answers the coder-agent decision "when do I stop hand-writing a prompt string and declare it as a `dspy.Signature`, and how do I name/describe its fields so the optimizer and the calling code both get a clean contract." Activate when: a prompt string grows past ~50 lines; the LM output is consumed by code (parsed, branched on, stored) rather than read by a human; the same prompt is reused across >1 call site; or a teammate asks "should this be a Signature?". Do NOT activate for one-shot throwaway prompts, or for HOW-TO questions about DSPy modules /optimizers/compile — defer those to the [[dspy]] skill and the [[agentsop-dspy]] workflow skill. Search keywords: typed prompt, structured prompt, DSPy Signature, prompt as a function, prompt contract, when to formalize a prompt.

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。

Triage the improvements backlog at .turbo/improvements.md: merge duplicate entries, state the user story or simplification behind each one, and decide with the user which to keep and which to drop. Use when the user asks to "triage improvements", "triage the backlog", "clean up the backlog", "clean up improvements", "groom the backlog", "prune the improvements backlog", or "go through the backlog with me".

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。

Clean up after (or abandon) a Rails upgrade. Drop NextRails.next? and NextRails.current? branches and retire dual-boot scaffolding (Gemfile.next, Gemfile.next.lock, conditional Gemfile groups), keeping either the next or the current version. Trigger when the user says they are done with the upgrade, want to clean up dual-boot, want to drop NextRails branches, want to finish the upgrade, want to abandon or revert the upgrade attempt, want to roll back to the current Rails version, or want to pause this upgrade hop. Based on FastRuby.io's "Finishing an Upgrade" methodology, extended with an abandon/pause path.

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。

Drive a PR to an approved code review by looping OCR's multi-agent review and address steps. Runs /ocr:review then /ocr:address repeatedly until the review verdict is APPROVE, then one final /ocr:address for leftover suggestions, posting every review and every address round to the GitHub PR as comments. Use when the user asks to 'review and address in a loop', 'iterate review until approved', 'auto review-and-fix this PR', 'loop /ocr:review and /ocr:address', or to take a changeset all the way to a clean APPROVE with the default reviewer team. Wraps the /ocr:review (.ocr/commands/review.md) and /ocr:address (.ocr/commands/address.md) skills; needs a feature branch with an open GitHub PR and the gh CLI for posting.

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。

Operate the `sno` command-line tool: install, update, check, and uninstall Sno products, read the exact commands and flags of the installed version, and run the account, skills, onboarding, Station telemetry and REM commands. Use when the owner or a task says "sno", "Sno CLI", "sno setup", "sno update", "sno doctor", "sno uninstall", "sno station", "telemetry consent", "rem verdict", "sno account", or "sno skills". The exact flags always come from the installed binary, never from this file. Do not use it to decide the owner's choices for them.

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。

Before showing the user any substantive GTM deliverable (positioning, value prop, homepage, launch post, pricing, sales script, the brief or roadmap), stress-test it against the standard as an independent critic, because the agent that wrote it is the worst judge of whether it is good. Use as a gate right before presenting work, or when the user asks whether something is actually strong.

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。

Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration. TRIGGER — read BEFORE opening the target file; don't skip because it "looks like a one-liner" — whenever: the prompt names Claude/Anthropic in any form (Claude, Anthropic, Fable, Opus, Sonnet, Haiku, `anthropic`, `@anthropic-ai`, `claude-*`, `us.anthropic.*`, `[1m]`); the user asks about an LLM (pricing/model choice/limits/caching) — never answer from memory; OR the task is LLM-shaped with provider unstated (agent/MCP/tool-definition/multi-agent/RAG/LLM-judge/computer-use; generate/summarize/extract/classify/rewrite/converse over NL; debugging refusals/cutoffs/streaming/tool-calls/tokens). SKIP only when another provider is being worked on (overrides all triggers): OpenAI/GPT/Gemini/Llama/Mistral/Cohere/Ollama named in the query; OR `grep -rE 'openai|langchain_openai|google.generativeai|genai|mistralai|cohere|ollama'` over the project hits (run this grep FIRST if no provider named — don't Read the file).

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。

Score a website's AI answer-engine visibility 0–100 against the open AIV rubric, and, with the user's own API keys, check and track through the OpenAI, Perplexity, Gemini and Anthropic APIs whether AI engines actually cite it. Use when the user wants to know whether AI engines can find, parse, trust and cite their site, or whether they do. Triggers on: 'does ChatGPT cite us', 'AI citation rate', 'share of voice in AI answers', 'track AI visibility weekly', 'AIV', 'AI visibility', 'GEO audit', 'generative engine optimization', 'AEO', 'llms.txt', 'will AI cite my site', 'AI search ranking', 'get cited by ChatGPT'.

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。

A terminal-native marketing system rendered entirely in Berkeley Mono — every word on the page, from the hero headline down to the footer fine print, is monospaced. The page itself reads like a manpage or a static-site README: warm cream canvas (`#fdfcfc`), nearly-black ink (`#201d1d`), 4px-radius rectangles for the few interactive elements, and bracketed `[+]`/`[-]` ASCII markers used as bullets. The brand's only "visual moment" is a single dark hero card that mocks up the OpenCode TUI itself — black background, monospaced terminal output, ASCII pipe characters, and a wordmark rendered as block-pixel ASCII. Every section sits as a hairline-bordered text block on the cream canvas with no shadows, no gradients, no decorative imagery, and no non-monospaced character anywhere in the system.

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。

The optional standing status report ("the weather"): compile open incidents, build health, merge-queue stats, and deploy lag into one always-current report page, and post to the channel only when a defined event fires. Use when the weather routine fires, or when someone asks to run/update the weather report.

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。

Captions living in 3D space around a talking head: a camera flies between the speaker and the words (whip-in, parallax truck, push), caption groups sit at different depths so camera moves pull them apart, hero words hide BEHIND the speaker through an alpha matte, a ring of words wraps round the speaker and turns in front of them, focus racks between depths, and text steps at 15 fps with ghost motion blur. Works in any type style (editorial serif, bold sans) or hand-drawn (p5.brush write-on). Trigger on: "3D text", "3D camera captions", "text around / behind the speaker", "camera moves through the text", "depth captions on my avatar video". Covers prep (portion, padded plate, matte, word clock, font metrics), the shot grammar, depth rules, QC, and limits.

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。

Thesis report synthesis — turn a thesis's markdown artifacts into its letter-size thesis-report.html, then OPTIMIZE it against real page renders. Four-step loop — pack (deterministic Python bundle of all sources + report/metrics.json), author (the LLM writes report/content.html — narrative, KPI tiles, badges, timeline, tables and citations are LLM judgment), assemble (deterministic validation, template injection, Q50 pins, Q47 overflow gate), render + optimize (Chrome headless per-page PNGs — the LLM reads them and iterates until every page is visually clean). Spec 046 Q46–Q50.

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。