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458,158 tools. Updated 2026-08-14 23:05

"Resources for Household Management" matching MCP tools:

  • Search Flevy's marketplace of consulting frameworks, PowerPoint templates, Excel financial models, business toolkits, and management case studies. Use this whenever a user needs a best-practice framework, methodology, template, financial model, or real-world case example on any business or management topic (strategy, digital transformation, supply chain, pricing, operational excellence, M&A, etc.). Returns up to 10 relevance-ranked recommendations across two content types: "document" (premium documents authored by management consultants) and "case_study" (management case studies). ALWAYS include each recommended item's url as a clickable link when you mention it in your reply — never reference a document without its link, because the link is the only way the user can open it. Each result carries a content_id for get_content_details. Filters: topic (single, or "topics" for documents covering ALL of several topics), author (list more documents from an author seen in results), filetype (including tier1_consulting_deck for McKinsey-style strategy decks), content_type. Topic-filtered responses also list related_topics to pivot to. Provide at least one of query, topic(s), or author; use list_topics to map user phrasing to a canonical topic.
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  • Read ONE entity with its sub-resources nested in a single call. Convenience over well_get_schema + well_query_records: resolves the field paths for you and returns the single record with its related data expanded. depth (relation-nesting BOUNDARY, 1-3, default 1): 1 = the entity + its direct sub-resources (emails, phones, locations, …) 2 = + the sub-resources' related scalars 3 = the full level-3 graph (LARGER payload — use when you need the whole picture) Stops at depth 3. Aggregates are excluded. Each child collection is capped at 50 rows; for a full list or to page a large child collection, use well_query_records on that child root instead.
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  • List pages in Redpanda API reference documentation. Returns endpoints, schemas, and topic pages with URL, title, type, and description. SCOPING (important for accurate results): - api="all" or omit: Lists all available APIs - api="admin": Cluster management operations (brokers, partitions, configs, users) - api="cloud-controlplane": Redpanda Cloud resource management (clusters, networks, namespaces) - api="cloud-dataplane": Cloud cluster data operations (topics, ACLs, connectors) - api="http-proxy": Kafka operations over HTTP (produce, consume, offsets) - api="schema-registry": Schema management (register, retrieve, compatibility) Use this to browse API structure. For general Redpanda docs, use ask_redpanda_question instead.
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  • Report the 30-day Amazon price-trend direction for a CPG category. Use when a pricing ops lead asks whether category pricing is rising, stable, or falling — e.g. setting retail promo calendar against an Amazon backdrop, deciding whether to raise wholesale prices during inflationary windows, or catching a price war before it spills into their channel. Returns: trend_direction (Rising / Stable / Falling / Insufficient Data), trend_window ("30 days"), confidence (note with product count), category (resolved name), last_refreshed, cta. Args: category: Exact category name — Grocery & Gourmet Food, Health & Beauty, Household, or Pet Supplies. Case-insensitive.
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  • Return this week's pending House Review recommendations (data gaps like a missing appliance warranty date or vehicle MOT date), re-validated live so items already filled in, actioned, or superseded by an open task are dropped before they're returned. Pro-gated: fails if the household isn't on a Pro plan.
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  • Check whether a trademark is FAMOUS — and, critically, famous FOR A SPECIFIC MARKET (you pass the applicant's Nice class as a PROXY for that market; fame is market-determined, there is no per-class fame doctrine). Fame is market-specific (Joseph Phelps Vineyards v. Fairmont): a mark famous for electronics is not automatically famous for fresh fruit. Returns is_famous, famous_in_class, the fame tier (broad/dilution-tier household name vs market-specific), the famous market footprint (expressed as Nice classes), portfolio size, and the corporate family's TTAB-as-plaintiff enforcement history. Use for "is X a famous trademark?", "is X famous for <goods>?", gauging a senior mark's §2(d) strength, or §43(c) dilution eligibility. It is a circumstantial signal, not statutory fame proof.
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  • Demand + rent-durability signals for a shortlist of US metros in ONE call — population & 5-year growth, renter share, median household income, and unemployment, straight from Census ACS. Deterministic by metro (CBSA-keyed) — NO FRED series-ID guessing. Pass `metros` ("City, ST", e.g. the top results from housing_market_screen). This is the Stage-2 "is the demand real?" filter on a yield shortlist — high yield in a shrinking metro is a trap. No API key needed.
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  • Return the kernelcad-authoring SKILL.md body — conventions for writing .kcad.ts scripts (imports, parameters, evaluation contract, common pitfalls). Use this tool BEFORE generating CAD code if your MCP client does not list resources. Clients that do list resources should instead read `kernelcad://skills/authoring` directly — the contents are identical. INPUT: none. OUTPUT: { uri, mimeType, text } where `text` is the SKILL.md body.
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  • Compare two cities for one household: take-home pay, full cost breakdown, the equivalent target salary needed to match source net cash, non-cash lifestyle deltas (vacation, parental leave, healthcare), and a 0-100 quality score on five weighted dimensions. Use this for a head-to-head between two named cities; for a single city call get_city_summary, and to rank many cities call rank_cities. Read-only, no side effects; returns a text summary plus structured JSON. RSU income is NOT a parameter; RSU is treated as source-only because grants typically do not follow you across employers.
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  • Generate Terraform (HCL) for EXISTING Control Plane resources from a self link. Single resource (`/org/acme/gvc/prod/workload/api`) or bulk by path depth — `/org/acme` exports the whole org, `/org/acme/gvc/prod/workload` exports every workload in a GVC. Set `generateImports` to get ready-to-run `terraform import` commands for adopting the resources into Terraform state, and `includeDependencies` to pull in referenced resources. Secrets are never exported — a ref that targets secrets is refused, and an export that would pull secrets in is refused wholesale. An unsupported kind is rejected with the supported list (list_terraform_kinds, full profile, enumerates them up front). For an in-memory manifest, use convert_to_terraform. Recommended reading: get_cpln_skill("iac-terraform-pulumi").
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  • Store a long-term memory about the household. Use sparingly for durable preferences, routines, constraints, or insights worth recalling in a future conversation. Recall first to avoid duplicates.
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  • Chilean open data catalogue (datos.gob.cl CKAN) — full metadata for a dataset by ID/slug: title, description, resources (download URLs + formats), organization, tags, and license.
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  • Return pricing-tier breakdown and category stats for an Amazon CPG category. Use when a brand is sizing up a shelf — e.g. evaluating whether a new SKU should enter at budget / midmarket / premium tier, benchmarking their retail pricing against Amazon tier structure, or preparing for a retail buyer meeting that will ask "what's the typical shelf price here?". Returns: category (resolved name), product_count (bucketed, e.g. "100+ products"), price_tiers (dict with budget / midmarket / premium dollar bands, rounded to nearest $0.50 for abstraction), median_price, trend_direction, last_refreshed, cta. Args: category: Exact category name — Grocery & Gourmet Food, Health & Beauty, Household, or Pet Supplies. Case-insensitive.
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  • Get CDC Social Vulnerability Index data for counties in a state. Returns overall SVI percentile ranking and all four theme breakdowns (socioeconomic status, household composition/disability, minority status/language, housing type/transportation) plus key indicator estimates for each county. SVI values range 0-1 (percentile ranking); higher = more vulnerable. Args: state: Two-letter US state abbreviation (e.g. 'WA', 'CA'). county_fips: Optional 5-digit county FIPS code to get a single county. year: SVI data year (default 2022, currently only 2022 available).
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  • Get the most vulnerable counties in a state ranked by SVI score. Returns counties sorted by highest SVI percentile ranking for the specified theme. Useful for identifying priority areas for grants and community health interventions. Args: state: Two-letter US state abbreviation (e.g. 'WA', 'CA'). theme: SVI theme to rank by. Options: 'overall', 'socioeconomic', 'household' (composition/disability), 'minority' (status/language), 'housing' (type/transportation). Default is 'overall'. limit: Number of counties to return (default 20, max 100).
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  • Get food-related economic indicators as proxies for food insecurity by county. Combines SNAP participation rate (B22001), poverty rate (B17001), and median household income (B19013) to build a food insecurity risk profile. Higher SNAP rates, higher poverty, and lower income correlate with greater food insecurity. Useful for grant narratives demonstrating community need. Args: state: Two-letter state abbreviation (e.g. 'WA', 'MS') or 2-digit FIPS code. county_fips: Three-digit county FIPS code (e.g. '033' for King County, WA). Omit to get all counties in the state. year: ACS 5-year estimate year (default 2022). Data covers year-4 through year.
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  • Get demographic data for counties: population, median age, race, Hispanic origin, income, and poverty. Returns one record per county with total population, median age, racial breakdown (White, Black, American Indian, Asian, Pacific Islander, Other, Two+), Hispanic/Latino percentage, median household income, and poverty rate. Args: state: Two-letter state abbreviation (e.g. 'WA', 'CA') or 2-digit FIPS code. county_fips: Three-digit county FIPS code (e.g. '033' for King County). Omit to get all counties in the state. year: ACS 5-year estimate year (default 2022). Data covers year-4 through year.
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  • Answers ONE question: whether stress is reaching US HOUSEHOLD balance sheets — not firms (corporate_transmission_board), not banks (failure_radar_board), not money-market plumbing (the Seiche sibling server). Read the Household Credit board: is stress transmitting through US household balance sheets? From free public data (FRED keyless): Fed quarterly delinquency and charge-off legs (card, consumer, mortgage, card charge-offs — level vs each leg's own trailing decade AND the yoy direction; falling never scores), G.19 revolving-credit velocity (two-sided — both tails historically meant stress), and the debt-service ratio as unscored context. The transmission thesis runs household -> corporate -> institution: this board confirms what the funding boards lead. Channels that cannot be read are listed in cannot_see, never reported as calm. Display-only: feeds no institution score and no watchlist tier. Returns ~4KB slim by default; pass full:true for thresholds, method prose and full sparklines.
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  • Read a resource by its URI. For static resources, provide the exact URI. For templated resources, provide the URI with template parameters filled in. Returns the resource content as a string. Binary content is base64-encoded.
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