「bid」の検索結果

Compare and analyze contractor bids. Score proposals, identify scope gaps, and recommend selections.

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Builds estimates, quotes, and bids for trades and field-service businesses (HVAC, plumbing, electrical, roofing, landscaping, painting, cleaning, remodeling, general contracting, IT/AV installs). Turns a scope into line items with waste factors, burdened labor, materials, equipment, subs, permits, mobilization, contingency, overhead, profit, and tax, then writes a client-ready xlsx (live formulas) and PDF plus an internal cost sheet, with good/better/best options, add-ons, a payment schedule, exclusions, and assumptions. Use whenever someone asks for a quote, estimate, bid, proposal price, or job price, asks "how much should I charge for this job", wants to check a price or margin on a job, or is confused about markup vs margin. Computes deterministically with a script instead of mental math, because models routinely treat a 30% markup as a 30% margin and drop labor burden, waste, and mobilization.

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Analyzes CRISPR drug-modifier (chemogenomic) screens with drugZ (Li & Hart 2019 Genome Med), a bidirectional Z-score method that identifies synthetic-lethal sensitizing genes and resistance-conferring suppressor genes from vehicle vs drug comparisons. Covers vehicle-anchored design (not Day-0), the bidirectional Z math giving 2-3x sensitivity over MAGeCK / STARS / edgeR / RIGER on drug screens, per-gene sumZ and normZ, synth (sensitizer) vs supp (suppressor) FDR, multi-dose handling, integration with control sgRNAs, and comparison with MAGeCK MLE with dose covariate. Use when running a drug-modifier CRISPR screen, identifying sensitizing or resistance genes for a drug candidate, choosing drugZ vs MAGeCK MLE for chemogenomic analysis, troubleshooting low-effect drug screens where MAGeCK lacks sensitivity, or designing a drug-screen layout (vehicle vs drug arms).

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投行并购 (投行并购 / 交易撮合 (Investment Banking M&A / Dealmaking) — 面向并购顾问、企业融资、卖方/买方交易执行的职业认知操作系统，从业者(分析师 Analyst / 经理 Associate / 副总裁 VP / 董事 Director / 董事总经理 MD / 内部公司发展 Corp Dev / PE 投资人)、想入行者、以及服务这行(法律/会计/估值/咨询)的视角。覆盖: (a) 第一性张力 — 投行 M&A 的核心世界观分歧: **价格 vs 价值 (price 是市场愿意付的, value 是内在的, deal 在两者缝隙里成交) ⇄ 确定性 vs 最高价 (certainty of close 对卖方常胜过纸面最高报价) ⇄ 顾问/中介 vs 委托代理 (banker 是 agent, 客户利益 vs 成交费的激励冲突真实存在, 「banker 总想成交」是行业原罪批判)**; 更深层 — 「过程/竞价纪律 (controlled auction 制造竞争张力、信息不对称管理) ⇄ 关系/信任 (relationship banking、长期 coverage、reputational capital)」, 「叙事/包装 (the story, equity story, positioning) ⇄ 数字/尽调 (the numbers, diligence, quality of earnings)」, 「估值的科学外衣 (DCF/comps 的伪精确) ⇄ 谈判的真实定价 (价格由 leverage、竞争、时机决定)」; (b) 估值与分析正典 (最标准化、最易蒸出高质量+CLI 化) — DCF (折现现金流: FCF 预测/WACC 折现率/terminal value 终值/Gordon growth vs exit multiple), Comparable Companies (可比公司/trading comps: EV/EBITDA, EV/Revenue, P/E), Precedent Transactions (先例交易/deal comps: control premium 控制权溢价), LBO (杠杆收购模型: IRR/MOIC/debt schedule/sources & uses), Accretion/Dilution (增厚/摊薄分析: EPS 影响、pro forma), Sum-of-the-Parts (分部估值/SOTP), Football Field (估值区间图), Merger Model (合并模型: synergies 协同/purchase accounting/goodwill), Sensitivity/scenario; (c) 交易流程与产出物 — 卖方流程 (sell-side: teaser 简介 → NDA → CIM/IM 信息备忘录 → management presentation → IOI 意向函 → data room 数据室 → LOI/term sheet → confirmatory diligence → SPA 买卖协议 → signing → closing), 买方流程 (buy-side: thesis/sourcing → outreach → valuation → bid → exclusivity → diligence → financing → close), auction 类型 (broad/targeted/negotiated/preemptive bid); 产出物: pitchbook 推介材料、CIM、fairness opinion 公平意见、board presentation、fee letter、engagement letter; (d) 交易结构与条款 — consideration (cash/stock/mix/earnout 对赌)、deal protections (breakup fee 分手费/go-shop/no-shop/MAC 重大不利变化条款)、representations & warranties 陈述与保证、escrow 托管、working capital adjustment 营运资金调整、reverse termination fee、collar 价格区间、tender offer vs merger、hostile vs friendly、defensive tactics (poison pill 毒丸/white knight 白衣骑士/staggered board); (e) 行业结构与角色 — bulge bracket (高盛/摩根士丹利/JPM/BofA/花旗) vs elite boutique (Centerview/Evercore/Moelis/Lazard/PJT/Perella) vs middle market (Houlihan Lokey/William Blair/Harris Williams) vs regional/independent; analyst→associate→VP→director→MD 晋升金字塔; coverage (行业组) vs product (M&A/ECM/DCM/leveraged finance/restructuring); sponsors group (服务 PE); 买方包括 PE/strategic acquirer/corp dev; (f) 量化指标与节奏 — deal fee (success fee 业内通常约 1-2% 视规模递减/retainer/Lehman formula)、league table 排行榜、pitch→mandate 转化、deal velocity、hours culture (analyst 80-100h/week 文化批判)、bonus/comp 结构、deal sheet (简历上的成交清单); (g) 争议/批判 — fairness opinion 是否橡皮图章 (利益冲突: 出意见的 banker 也收成交费)、estimate 的伪精确 (DCF garbage in garbage out、假设驱动结论)、banker 永远建议成交 (deal 偏见、empire building 助推 CEO 自利并购)、协同效应系统性高估 (大量并购毁灭价值、winner's curse 赢家诅咒)、analyst 血汗工厂文化 (2021 高盛 13 人 deck 事件、过劳死争议)、advisory 价值 vs 中介寻租之争、bulge vs boutique 的利益独立性叙事 (boutique 标榜「无承销利益冲突」)、SPAC 泡沫与 de-SPAC 教训; (h) 流派/思想谱系 — 估值学派 (Aswath Damodaran 估值教父/纽大、Tim Koller McKinsey《Valuation》、McKinsey valuation 体系) vs 公司金融教科书派 (Rosenbaum & Pearl《Investment Banking》行业圣经、Brealey Myers Allen、CFI/WSP/BIWS 培训体系) vs 交易实战派 (Bruce Wasserstein《Big Deal》、Joseph Perella/Felix Rohatyn 老派 dealmaker、现代 boutique 创始人) vs 行为/批判派 (并购毁灭价值的学术证据、Damodaran 对协同/控制权溢价的批判、Matt Levine《Money Stuff》解构华尔街逻辑) vs PE/buy-side 视角 (LBO 数学、value creation 杠杆/运营/multiple expansion)。不含: 二级市场股票交易/卖方研究 (equity research)、零售财富管理/private banking、纯 ECM/IPO 承销执行 (虽相关但聚焦 M&A advisory)、纯 PE 投后运营、量化交易/对冲基金策略、纯公司财务报表会计。) Master OS — automated mastery of 投行并购 / 交易撮合 (Investment Banking M&A / Dealmaking) — 面向并购顾问、企业融资、卖方/买方交易执行的职业认知操作系统，从业者(分析师 Analyst / 经理 Associate / 副总裁 VP / 董事 Director / 董事总经理 MD / 内部公司发展 Corp Dev / PE 投资人)、想入行者、以及服务这行(法律/会计/估值/咨询)的视角。覆盖: (a) 第一性张力 — 投行 M&A 的核心世界观分歧: **价格 vs 价值 (price 是市场愿意付的, value 是内在的, deal 在两者缝隙里成交) ⇄ 确定性 vs 最高价 (certainty of close 对卖方常胜过纸面最高报价) ⇄ 顾问/中介 vs 委托代理 (banker 是 agent, 客户利益 vs 成交费的激励冲突真实存在, 「banker 总想成交」是行业原罪批判)**; 更深层 — 「过程/竞价纪律 (controlled auction 制造竞争张力、信息不对称管理) ⇄ 关系/信任 (rela

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。

Hedges' 4-kind lattice for bidirectional programming - covariant/contravariant/invariant/bivariant types with GF(3) correspondence

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Generate a complete subcontract from a firm's template, awarded bid, and project specs. Outputs a Word document. Triggers: 'subcontract', 'sub agreement', 'write contract', 'draft subcontract'. Requires awarded bid.

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"Apply organizational ambidexterity theory to balance exploration and exploitation activities. Use this skill when the user needs to diagnose whether an organization is over-exploiting or over-exploring, design structures that support both innovation and efficiency, or evaluate the tension between short-term performance and long-term renewal.".

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Full-funnel paid advertising operations for B2B SaaS. Use this skill for PPC strategy, Google Ads optimization, LinkedIn Ads, social media advertising, programmatic buying, creative strategy, attribution modeling, budget allocation, budget pacing and planned-vs-delivered reconciliation, audience overlap and campaign self-competition audits, suppression lists, ROAS improvement, media spend optimization, and the media no auction sells — newsletter and podcast sponsorships, community and industry-publication placements, paid review-site listings on G2 and Capterra, and pay-per-lead content syndication. It also covers buying on the AI answer surface — ads inside Google AI Overviews and AI Mode that existing Search, Shopping and Performance Max campaigns already serve into with no opt-out, no placement targeting and no segmented reporting, and ChatGPT Ads and Microsoft Copilot as separate opt-in platforms with their own plan-tier reach limits, no negative keywords, and a landing-page crawler gate. It also owns the conversion signal the bidding algorithms learn from — CRM pipeline stages (SQL, opportunity, closed-won) sent back to Google Ads, LinkedIn, Meta and Microsoft Ads through offline conversion import, enhanced conversions for leads, the Google Data Manager API and the LinkedIn Conversions API, with click-ID capture, stage values, dedupe, EEA consent signals and retractions. It also gates connected TV (CTV) and streaming video for B2B — whether a reach medium belongs in the plan, how a vendor ties a TV household to a target account (member data, IP-to-account graph or contextual), the server-side ad insertion (SSAI) fraud questions, Programmatic Guaranteed deals, and a holdout lift test because CTV has no click. It also runs person-led paid social — LinkedIn Thought Leader Ads and Meta partnership ads that put spend behind an employee's or creator's post — on a paid-usage term, an in-post disclosure check and an end-date register, because the platform approval carries no term. Also triggers on: CTV, connected TV, OTT, streaming TV ads, should we run CTV, LinkedIn CTV, B2B CTV, account-based CTV, SSAI fraud, thought leader ads, boost an employee's post, sponsor a creator's post, partnership ads, whitelisting, creator usage rights, PPC, Google Ads, LinkedIn Ads, social ads, programmatic, ad creative, attribution, media budget, paid campaigns, ROAS, CPA, ad spend, newsletter sponsorship, podcast sponsorship, community sponsorship, sponsor a newsletter, content syndication, pay-per-lead, cost per lead vendor, media kit, rate card, insertion order, direct buy, publisher partnership, make-good, G2 paid listing, Capterra ads, review site advertising, sponsorship ROI, budget pacing, we underspent our budget, are our campaigns competing with each other, audience overlap, self-competition, campaign cannibalization, suppression list, exclusion list, ad frequency across channels, how many ad accounts do we have, ads in AI Overviews, AI Mode ads, ChatGPT Ads, OpenAI Ads Manager, Copilot ads, conversational ads, should we advertise on ChatGPT, can we buy our way into the AI answer, our ads are showing in AI Overviews and we cannot report on it, context hints, OAI-AdsBot, our ad landing page fails review, robots.txt is blocking our ads, our paid leads are junk, Google Ads is optimizing for the wrong leads, offline conversion import, OCI, enhanced conversions for leads, send CRM stages back to Google Ads, upload SQLs to LinkedIn, LinkedIn Conversions API, LinkedIn CAPI, Meta conversion leads, CRM to ad platform, gclid, li_fat_id, msclkid, value-based bidding, optimize for pipeline not form fills, low match rate, conversion lag.

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Plan and review paid-media budgets, bidding, pacing, marginal return, forecasts, CPA, ROAS, MER, LTV:CAC, constraints, and allocation across supported platforms. Use for ad budget allocation, media budget, bidding strategy, scaling, spend pacing, budget forecast, ROAS target, or investment tradeoffs.

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Diagnoses Google Ads account performance issues such as conversion loss (value or volume), low lead flow/volume, and lost impression share (opportunities) due to ad rank, bids, or budgets. Use when troubleshooting sudden performance drops, analyzing campaign impression share metrics, investigating low lead flow, or searching for bidding and budget constraints. Don't use for setting up new campaigns, uploading conversion events directly, or general Google Mobile Ads SDK integration issues (use gma-android-integrate instead).

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Draft and send client proposals via [Better Proposals](https://composio.dev/toolkits/better-proposals) or [Bidsketch](https://composio.dev/toolkits/bidsketch)

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Complete construction estimating and cost management system. Use when preparing project estimates, bid proposals, cost breakdowns, value engineering, change order management, or construction budget tracking. Covers residential, commercial, and infrastructure projects. Trigger on 'estimate', 'construction cost', 'bid', 'takeoff', 'cost breakdown', 'change order', 'value engineering', 'construction budget', 'unit pricing', 'RSMeans'.

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Analyzes CRISPR drug-modifier (chemogenomic) screens with drugZ (Colic et al. 2019 Genome Med), a bidirectional Z-score method that identifies synthetic-lethal sensitizing genes and resistance-conferring suppressor genes from vehicle vs drug comparisons. Covers vehicle-anchored design (not Day-0), the bidirectional Z math giving greater sensitivity to small-effect hits than MAGeCK / STARS / edgeR / RIGER on drug screens, per-gene sumZ and normZ, synth (sensitizer) vs supp (suppressor) FDR, multi-dose handling, integration with control sgRNAs, and comparison with MAGeCK MLE with dose covariate. Use when running a drug-modifier CRISPR screen, identifying sensitizing or resistance genes for a drug candidate, choosing drugZ vs MAGeCK MLE for chemogenomic analysis, troubleshooting low-effect drug screens where MAGeCK lacks sensitivity, or designing a drug-screen layout (vehicle vs drug arms).

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This skill suggests follow-up tests for specific comorbidities associated with Cushing's syndrome in patients with adrenal adenoma when CT density is less than 10 Hounsfield units. Use when managing a post-adrenalectomy Cushing's syndrome patient with confirmed adrenal adenoma pathology and low-density imaging (<10 HU).

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This skill directs lifelong treatment of cardiovascular risk factors, osteoporosis, and psychiatric symptoms in all patients with Cushing's syndrome until biochemical resolution of hypercortisolism. Use when managing any CS patient for long‑term comorbidity control; triggers include persistent hypertension, dyslipidemia, low bone density, depression, anxiety, or cognitive changes in the setting of known or suspected CS.

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This skill recommends that all patients with Cushing’s syndrome receive monitoring and adjunctive treatment for cortisol-dependent comorbidities including psychiatric disorders, diabetes, hypertension, hypokalemia, infections, dyslipidemia, osteoporosis, and poor physical fitness. Apply when managing any CS patient to address associated health issues; triggers include confirmed or suspected hypercortisolism, preoperative evaluation, postoperative follow‑up, or persistent hypercortisolism despite treatment.

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Suggests a trial of dehydroepiandrosterone (DHEA) replacement in women with primary adrenal insufficiency (PAI) who report low libido, depressive symptoms, and/or low energy levels despite otherwise optimized glucocorticoid and mineralocorticoid replacement. Consider when a woman with PAI presents with persistent low libido, depressive symptoms, and/or low energy levels after glucocorticoid and mineralocorticoid doses have been titrated to clinical targets.

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Web サーバ（nginx/apache、Linux 中心）の Phase 1 設定セキュリティレビュー。 target_profile.yaml で対象を確定し、MANIFEST.txt + manifest_attestation.txt で証跡 integrity を検証。 SSH 直接または証跡受領モードで 9 観点 (OS/リソース/ログ/ネットワーク/サービス/認証/監視/バックアップ/証明書) を read-only 走査。6 階層ガード (allowed/conditional/conditional_sensitive/ask-first/exceptional_sensitive_read/forbidden)、 3 軸補助 (Exploitability/Blast Radius/Service Criticality) の重大度判定、 observation_status による未確認の独立管理、evidence_dir/raw_evidence_store 分離、自己レビュー必須。 Windows/IIS は v1 hard fail。 Use when: Web サーバの設定セキュリティレビュー、Phase 1 監査、nginx/apache 構成監査、 EOL ランタイム調査、ログローテーション不備調査、ドキュメントルート漏えい調査。

再発しやすい危険な実装パターンを、安全側に倒れる標準パターン・禁止事項・共通層・静的ルール候補へ 変換するスキル。ORM強制、deny-by-default認可、サービス経由I/O、永続化確認後の成功表示などを設計する。 レビューで危険コードを見つけるのではなく、危険コードを書きにくくする設計標準を作ることが目的。 Use when turning repeated defect patterns into safe architectural defaults, forbidden-to-safe mapping tables, common layer designs, and enforceable static analysis rules.

Drafts answers to the questions in a received RFP, RFQ or tender from the organisation's past responses, answer library, case studies, policies and other documents provided: one row per buyer question with a draft answer marked Reused, Adapted or Missing, its source and date, and a legal or pricing review flag on every answer touching terms, liability, warranties, insurance, data protection or price. Use when the user asks to "draft our RFP response", "answer this tender from our past proposals", "pre-fill the bid questions", "first pass at the RFQ answers" or "reuse our previous bid content". Do not use for writing the buyer's own RFP or requirements, use rfp-requirements-pack instead; for security or due diligence questionnaires use vendor-security-questionnaire-prefill; for scoring received supplier responses use rfp-comparison-pack. Drafts for human review; never approves, authorises or signs off.

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Builds a DRAFT weighted supplier evaluation matrix from supplier responses and the panel's agreed criteria, weights and scale: a provisional score per cell with the quoted evidence and anchor behind it, a register of every missing or partial answer, and calibration and sensitivity flags. Provisional for panel moderation; never recommends, awards or disqualifies. Use when the user asks to score, weight or rank supplier, bid or tender responses against agreed criteria, for example "score these bids", "build the evaluation matrix", "weight the tender responses" or "rank the suppliers against our criteria". Do not use for a side-by-side comparison without scores, use rfp-comparison-pack instead; for writing the criteria, use rfp-requirements-pack instead. Drafts for human review; never approves, authorises or signs off.

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GitHub Actions の CI 失敗を調査するスキル。失敗した run / PR / job の URL（例: https://github.com/OWNER/REPO/actions/runs/RUNID、…/pull/PR、…/job/JOBID）や run_id・PR 番号を貼られて「このCIが失敗している、原因を調査して」「ビルド/テストがコケた、なぜ落ちたか調べて」「workflow が failed、修正案を出して」「job のログを見て」と頼まれたら必ず使う。WebFetch では github.com のログは取れない（PreToolUse hook が差し戻し、HTML しか返らない）ため、gh（`gh run view --log-failed` / `gh run view --job` / `gh pr checks` / `gh api`）で失敗ジョブ・ステップと失敗ステップのログだけを決定論スクリプトで収集し、失敗原因を特定して修正案を提示する。GitHub Actions 以外（GitLab CI 等）や、URL がログではなくソース閲覧目的のときは対象外。GitHub(gh) 前提。`/gh-ci-investigate` で明示起動も可。

Use when the user asks to "plan launch pricing", "design pricing tiers / packaging", or "set up a launch discount / early-bird offer"; produces a launch pricing and packaging plan — tier structure and naming, a value-to-price map aligned to the message house, a launch-offer ladder with a true deadline reason, beta / early-adopter pricing with a post-launch graduation path, and guarantee / refund terms — with every price claim and offer term submitted to memory/events/claims.ndjson. Not for the canonical offer / claim record — use offer-claims-registry; not for paid-newsletter subscription economics — use newsletter-monetization-planner; not for ad bidding — use bid-strategy-planner. 发布定价/梯度打包/早鸟优惠/保证设计

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Use when the user asks to "check pacing", "am I over/under-spending", "is this campaign on track to hit budget", or "why did spend spike/stall mid-flight"; returns a spend-vs-target-curve read, learning-phase status, an over/under-delivery call, and a reallocation trigger. Not for initial budget allocation — use budget-optimizer; not for choosing the bid strategy — use bid-strategy-planner; not for the RQS gate — use ad-account-auditor. 付费广告预算节奏监控/跑量过快过慢/在途配速

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