Results for “basket-drafting”

Lightweight ContentShake AI self-check the /draft stage can call before saving. Returns just SEO + Quality scores (no full optimization) so the writer knows whether the draft is in winning territory before /quality-check runs. Fails soft when SEMRUSH_API_KEY is unset.

Drafts clear, professional emails ready to copy and paste — from a brief description of the situation, audience, and intent. Use when asked to write, draft, or compose an email, reply to a message, or suggest how to phrase something professionally.

Draft outcome-led value proposition hooks for a target agency or pursuit using vault context and mission alignment. Use when user asks for messaging angles for capture — catalog skill from coreyhaines marketingskills pattern.

Draft a clear, complete, ready-to-send offer letter with compensation, terms, and contingencies — flagging every unconfirmed figure.

Benchmark-relative quality gate. Scores the draft against the research dossier's beat spec (depth, consensus coverage, evidence) plus AI-tell and voice signals, runs an adversarial read armed with the SERP benchmark, and emits the verdict that gates the pipeline.

Draft a professional, audience-aware email or reply with calibrated tone and a clear call to action. Use when the user needs one message, response, follow-up, support note, or meeting request; use sales-email-sequences for a coordinated multi-touch outbound campaign.

Drafts professional emails that match your personal writing style by analyzing sent emails for tone, greeting, structure, and sign-off patterns.

Use when a writer wants to improve a draft through guided questioning and revision rather than a direct rewrite

Matryoshka Representation Learning

Post-draft pass that expands a drafted article to capture the FULL keyword family — keywords the page already or could rank for, plus the Ahrefs Content Gap (keywords competitors rank for but we don't) — by weaving the worthwhile ones in as natural added paragraphs/sections. NOT keyword stuffing. Triggered after /draft, before /quality-check.

Find sources for every numerical claim in the draft, add inline hyperlinks, and add internal links to brand-reference articles. Triggered after /draft.

Layer 4 of the keyword research pipeline. Spawns a "skeptical SEO" adversarial sub-agent to argue against every survivor of Layers 1-3. Catches mechanical-classifier blind spots — wrong SERP intent, hidden link-graph gauntlets, AIO trajectory shifts, vanity-rank metrics. Same pattern as quality-check's adversarial draft read, applied to keyword selection.

Draft, rewrite, or condense emails with target tone, length, and audience; use for cold outreach, replies, status updates, or escalations where clarity and brevity matter.

The choice is not about scale or sophistication.

Draft, rewrite, or condense emails with target tone, length, and audience; use for cold outreach, replies, status updates, or escalations where clarity and brevity matter.

This skill should be used when the user asks to "create an index", "build a basket of top assets", "buy a weighted basket", "make a portfolio of assets", "equal-weight basket", "rebalance my portfolio", "track the top N tokens", or wants an automated, weighted multi-asset basket that buys in one pass and rebalances on a cadence. Builds the basket spec, delegates each buy and rebalance swap to the swap-integration Trading API flow, and records target weights in state.

Expand an annotated outline into full article prose using brand voice anchored in example articles, hitting the outline's per-section depth targets. Triggered after /product-mentions.

Organize email inbox, draft replies, send messages, and verify delivery with evidence-based confirmation.

Write a useful, author-consistent article and substantively improve it before verification.

Rank an existing set of context chunks by relevance, diversity, freshness, and utility. Use when retrieval has already produced candidates that must be scored or reranked; use context-retrieval when the source corpus still needs to be searched.

Find adjacent vendors and subs (not top market primes) who fill a capability gap against a displacement target using USASpending flows and SAM entity signals. Use when user defines a teaming gap and wants vault-ready partner shortlist with citations.

Scaffolds fullstack projects (Next.js, FastAPI, MERN, Django) and analyzes code quality with security and complexity scoring.

Track key contacts who change jobs and draft warm outreach to movers at ICP companies

Draft or revise a scene on a goal-conflict-disaster spine with sensory grounding.

Craft Fleet

Compare Itô prediction-market baskets against a user's knowledge base, portfolio notes, financial context, watchlist, or research thesis for read-only gap analysis.

Draft a legal document — a pleading, motion, brief section, or contract clause — with verified citations, flagged assumptions, and mandatory supervisor review before filing.

Selects a minimal, non-redundant set of facts, artifacts, skills, and references for a working decision when context is stale, uncertain, or over budget.

Symbol Database Selection Pattern

Skeptical pushback on the outline before drafting starts. Asks whether the outline is MECE, BLUF, problem-agitate-solution; whether it covers the topic better than the SERP top-5; whether sections duplicate; whether each section earns its visual. One revision pass on FAIL (BLOG_AGENT_OUTLINE_REVISION_BUDGET, default 1).

End-to-end Kaggle competition workflow for scored submissions, covering code competitions, validation, metrics, public notebook/discussion intel, tabular/text/image modeling, tuning, ensembling, multi-notebook architectures, Kaggle GPU offload, and hidden-test debugging.

Routes writing tasks to the correct voice playbook by reading a voice selection authority file fresh on every call, classifying the task into one of 22 content types, and returning a load list with crossover budget and phrasebook section.

Build a USASpending relationship snapshot for the incumbent and buying agency on a pursuit row. Use when user needs award flows and rel counts before battlecard or teaming work — deterministic from DuckDB bulk.

Evaluates an AI judge system's pairwise ranking accuracy on generated commit messages against a heuristic ground truth from five automatic text metrics, using the MCMD dataset.

Draft privacy-policy language and a review checklist tailored to a business model, data practices, and relevant jurisdictions. Use when the user requests a privacy policy or needs to map disclosures for GDPR, CCPA, or similar frameworks; do not use it to guarantee legal compliance.