Claude Skills by mcorbett51090

Decompose staffing margin into bill minus pay minus burden, itemize the burden stack, and locate whether a compression is pricing, pay, burden, or mix — before anyone calls it a pricing problem. Reach for this when gross margin or spread is moving and the cause is unclear.

Build a segment-by-segment competitive-positioning analysis for a staffing firm — placing it on a players-by-segment grid, naming where it wins and where scale competitors lead, with a source on every claim. Reach for this when the question is where the firm is strong vs. losing in the competitive set.

Design or audit the credentialing and clearance pipeline as a measured part of time-to-fill, with stage timings, document-completion gates, and the parallelizable steps that compress time-to-start. Reach for this when time-to-start lags time-to-offer or fall-off concentrates between accept and start.

Diagnose a fill-rate move without blaming the wrong thing — by pinning the denominator, checking the seasonal boundary, splitting supply from order-quality, and pairing with time-to-fill including the credentialing clock. Reach for this when fill rate dropped and the cause is unclear.

Locate where the recruiting pipeline leaks by decomposing it stage by stage (order to workable to submittal to interview to offer to accept to start to billing), naming the leak stage and its likely cause. Reach for this when placements or submittal-to-fill are down and you need to find where candidates fall out.

Lay out a staffing KPI dashboard so the most decision-relevant number is read first, every tile pairs with its partner metric, and a red number explains itself via drill-down. Reach for this when turning a scorecard spec into a dashboard layout (not the build — the design).

Right-size a recruiting desk by modeling fillable-order supply against the reqs a recruiter can carry at target conversion, distinguishing nominal from fillable orders and under-fed from under-staffed. Reach for this when the question is whether to hire more recruiters or whether the team is the right size.

Produce a staffing readout that compares like-cycle-to-like-cycle instead of calendar-quarter-to-calendar-quarter, so the academic or healthcare seasonality doesn't masquerade as a performance change. Reach for this when a fill-rate or volume comparison crosses a seasonal boundary.

Build a staffing operations scorecard where every KPI carries a definition, formula, window, baseline, owner, drill-down, and a triggered action — so an operator can act on it Monday morning. Reach for this when standing up a new scorecard or auditing one that reports numbers nobody acts on.

Produce a defensible staffing market-trend readout — segment-resolved, SIA-anchored, triangulated across primary sources, with the inflection (not just the level) named and soft numbers marked. Reach for this when a client wants the market read for healthcare and/or education staffing.

Build a tiered, stage-fit investor pipeline and a warm-intro-first outreach sequence for a founder running a round. Produces a target list scored by stage-fit + thesis-fit + check-size, a warm-path map for each target, and a sequenced outreach plan that builds momentum. Reach for this when the user asks "who should I pitch?", "build my investor list", or "how do I run outreach?". Used by `fundraising-strategist` (primary); coordinated with `pitch-and-narrative-coach`.

Model a startup cap table and the dilution a round causes — including option-pool shuffle, pro-rata, and post-money SAFE conversion — with worked arithmetic. Produces a post-round ownership table and surfaces the post-money-cap dilution gotcha. Reach for this when the user asks "what does my cap table look like after this round?", "how much do I get diluted?", "how does my SAFE convert?", or "what option pool should I set aside?". Used by `fundraising-strategist` (primary).

Assemble a founder's fundraising data room — the structured set of documents investors expect in diligence — so a "send me the data" request never stalls the round. Produces a stage-appropriate checklist organized by section (corporate, financials, cap table, product/tech, traction, team, legal/IP) with a what-to-include and a what-to-redact note per item. Reach for this when the user asks "what goes in a data room?" or "I got a diligence request — am I ready?". Used by `fundraising-strategis...

Hit a live-streaming latency target: pick the approach (standard HLS/DASH, LL-HLS/LL-DASH with chunked CMAF, or WebRTC for sub-second/interactive) from the required end-to-end latency and scale, then budget latency across capture/encode, segment & part duration, chunked transfer, live origin, CDN, and the player live-edge buffer — trading latency against rebuffer risk deliberately. Protocol/latency specifics verify-at-use.

Deliver playback quality-of-experience: integrate the player (hls.js / dash.js / Shaka / ExoPlayer / AVPlayer) to the chosen protocol and DRM, tune the ABR algorithm (buffer- vs throughput-based, start bitrate, switch thresholds, caps) for stability, measure QoE by rebuffer ratio / startup time / average bitrate / VSF, and tune CDN/edge cache (cache-key, TTL, prefetch) — all instrumented with playback analytics. Player/CDN/QoE specifics verify-at-use.

Choose VOD vs live and the streaming protocol (HLS / MPEG-DASH / CMAF / LL-HLS / WebRTC) on the use-case, latency target, and device/browser reach — then commit to a packaging format (CMAF hedge), an origin/edge design, a single-vs-multi-CDN strategy, and the multi-DRM matrix (Widevine / FairPlay / PlayReady) the reach implies. Protocol/DRM/CDN specifics verify-at-use.

Choose codecs in tiers (H.264 reach floor + HEVC/AV1/VP9 efficiency), design the ABR ladder per-title from content complexity rather than a fixed table, build the FFmpeg pipeline for the quality/throughput/cost triangle (CRF vs 2-pass, GPU vs CPU, chunked parallel, GOP/segment alignment), and package once to CMAF/fMP4 with captions and loudness-normalized audio. Codec/flag/bitrate specifics verify-at-use.

Design and automate failed-payment recovery (dunning) — retry schedule, smart/adaptive retries, grace period, customer comms sequence, and entitlement-downgrade policy — trading recovered revenue against churn of good customers. Use for involuntary-churn reduction.

Implement usage-based / metered billing correctly — idempotent usage recording, aggregation & rating to billable quantities, on-time usage reporting before invoice close, and counted-vs-billed reconciliation. Use when billing on API calls, seats used, GB, events, or any consumption metric.

Model the plan / price / entitlement structure for a recurring-billing system — choose flat vs tiered vs per-seat vs usage/metered vs hybrid, define entitlements, and set proration/trial/coupon rules. Use when starting a billing build or re-pricing an existing product.

Build a defensible demand forecast: traverse the forecast-method selection tree, clean demand history, select and fit the statistical model, measure MAPE and bias on a holdout period, design the consensus overlay process, and hand off the error distribution to inventory policy.

Set a defensible inventory policy: segment SKUs with ABC/XYZ, select the replenishment method per segment, calculate safety stock from the service level and variability inputs, calculate reorder point and EOQ, and quantify the working-capital tradeoff.

Design or facilitate the monthly S&OP/IBP cycle: run the five-step gate sequence (product review → demand review → supply review → pre-S&OP reconciliation → executive S&OP), produce the gap analysis, build scenarios, and close the cycle with a decision record.

Step-by-step runbook for promoting Tableau workbooks and data sources from development through test to production using the Content Migration Tool, REST API, and tabcmd — with pre-promotion checklists, rollback steps, and the governance gates that prevent silent data breaks. Owned by tableau-admin.

Checklist-driven review for Tableau dashboard layout, chart-type selection, formatting, and accessibility — covering the question-first design principle, attention hierarchy, filter placement, colour and font conventions, and the five layout anti-patterns that confuse users. Owned by tableau-viz-engineer.

A step-by-step setup for secure Tableau embedding with a Connected App (Direct Trust) + a server-minted JWT and the Embedding API v3 — minting the right claims, scoping the token, and binding the JWT identity to the RLS entitlement key. Use when embedding a viz in an app with per-user or per-tenant data isolation. The auth verdict escalates to ravenclaude-core/security-reviewer.

Playbook for diagnosing and fixing slow Tableau workbooks: the measurement-first approach, the six extract optimisation levers, query performance recording interpretation, and the view-level and data-source-level fixes that address 90% of performance complaints. Owned by tableau-data-architect.

Step-by-step playbook for diagnosing the grain mismatch that causes wrong numbers, then selecting and constructing the right LOD expression (FIXED, INCLUDE, EXCLUDE) or table calculation. Includes the LOD-vs-table-calc decision, worked examples, and the common double-counting fixes. Owned by tableau-viz-engineer.

Gate-by-gate checklist for designing Tableau row-level security (RLS): mechanism selection (user filter vs entitlement table vs data-policy VDM), implementation verification, performance impact assessment, and the mandatory security-reviewer escalation criteria. Owned by tableau-admin.

A repeatable, evidence-first Tableau workbook performance audit — run the Performance Recorder, read the longest events, and apply the right lever per dominant event category (Executing Query / Computing / Rendering / Connecting). Use when a workbook or dashboard is slow and you need the cause, not a guess.

Respond to an IRS/state notice and run the planning calc by traversing the practice decision tree (identify the notice type & deadline → reconcile the agency figures vs the return → agree/partial/disagree response + substantiation → representation posture: handle vs refer; and for planning: entity-choice SE-tax vs S-corp reasonable-comp → QBI/§199A → retirement & timing levers as scenarios), then return the notice-response plan or the planning scenarios with assumptions and the verify-against...

Plan the client mix, open the engagement, and size busy-season capacity by traversing the practice decision tree (engagement accept/decline & risk screen → client-mix/niche → engagement letter + organizer scope → busy-season volume × preparer-hours vs reviewed-hours → extension policy as load valve → pricing/realization model), then return the accept/decline call, the engagement letter & organizer scope, the capacity/staffing plan, and the pricing model with the conditions that resize it. Rea...

Run a return from organizer through e-file by traversing the practice decision tree (organizer & completeness check → entity→form routing: 1040 / 1120 / 1120-S / 1065 → preparation & schedules → self-review vs a separate-reviewer gate → e-file & acknowledgment → extensions 4868/7004 & quarterly estimates), then return the prepared return, the completeness gaps, the review findings, the e-file path, and any extension/estimate schedule. Reach for this when the user asks 'prepare this 1040 / 112...

Define and track a project that spans multiple GitHub repos. Use when a piece of work (a launch, a client, a feature) lives across several repositories and you want its status rolled up in one place instead of checked repo-by-repo. Covers the three match rules (repo / label / title-prefix), how an event is attributed to a project, choosing a convention that scales, and reading the per-project status the report and dashboard produce.

Analyse the portfolio activity data to identify cross-team contributors, unmatched activity, and load distribution across repos and people. Reach for this skill when a supervisor wants to understand who is contributing where across the team's repos, or when the portfolio output shows unexpected activity patterns.

Review and tighten the GitHub token scope and hub-repo access configuration for a team-portfolio deployment. Reach for this skill during any security audit, when a team member leaves, when new repos are added to the tracked list, or when a 403 error appears in the collection log.

Stand up centralized multi-repo, multi-person activity tracking for a team. Use when a team works across several GitHub repos and needs one place to see who did what — and a supervisor needs a manage-the-team roll-up that a single-repo activity log can't provide. Walks choosing a hub repo, writing team-portfolio.json (repos + roster + cross-repo projects), wiring the scheduled GitHub Action and the on-demand command, picking a GitHub token, and optionally enabling a hand-maintained narrative ...

Tune the portfolio-tracker scheduled Action cadence, collection-window-days, and report output settings to match the team's actual review rhythm. Reach for this skill when the weekly tracker is generating too much noise, when the window produces gaps or double-counts, or when the supervisor wants a different report frequency.

Build the cross-team dependency graph and derive the critical path — every handoff gets a producer, consumer, due date, and interface contract; cycles and single points of failure get flagged. Use when a program spans multiple teams and you need to know what actually decides the date.

Run a go/no-go launch-readiness review against written, pre-agreed criteria and design a staged rollout with a tested rollback. Use as a launch approaches — define measurable, owner-assigned criteria first, then facilitate the decision and record any waiver with its risk acceptance.

Turn a fuzzy cross-team mandate into a chartered program — a measurable outcome, a named sponsor, explicit in/out-of-scope boundaries, the teams on the hook, and the starting RAID. Use at the very start, before any planning, whenever a multi-team effort lacks a clear outcome or owner.

Diagnose what to fix first for a described site by walking the SEO strategy decision tree (crawl → render → index → understand → rank), fixing the lowest broken rung first, then return the priority diagnosis, the indexation strategy, the E-E-A-T posture, and the conditions that would reorder the priorities. Reach for this when the user asks "our organic traffic is flat — where do we start?", "what should we fix first for SEO?", "which pages should we index or noindex?", or "how do we rank in ...

From a site's target queries and page classes, design the crawl-efficient information architecture (flat depth, hub-and-spoke topic clusters), the internal-linking model that flows authority to the money pages, and the topical-authority / entity map that tells search engines what the site should own. Reach for this when the user asks "how should we structure the site and internal links?", "design our topic clusters / content model", or "what's our topical-authority / entity map?". Used by `se...

Implement and verify the technical-SEO layer for a site — crawlability (robots.txt, XML sitemaps, log-file analysis), rendering (CSR→SSR/SSG/prerender), indexation controls (canonical, meta-robots noindex, hreflang), JSON-LD schema.org structured data for rich-result eligibility, Core Web Vitals (INP/LCP/CLS on field data), and redirect-mapped site migrations — each checked against GSC / URL Inspection / the Rich Results Test / server logs. Reach for this when the user asks "fix our crawl/ind...

Write trustworthy developer reference: drive it from the spec (OpenAPI/AsyncAPI) so it can't drift, make every example runnable, document the unhappy path (errors/limits/auth/pagination), and optimize the quickstart for time-to-first-success.

Practical guide for classifying documentation into the four Diataxis quadrants (tutorial, how-to, reference, explanation) — with a decision checklist, anti-pattern catalog, and remediation moves.

Apply the Diataxis framework: identify which of the four documentation kinds you're writing (tutorial/how-to/reference/explanation), keep them separate, and organize the whole docs set around the reader's journey rather than the system's structure.

Run docs like software: pick the tooling by needs (Docusaurus/Mintlify/MkDocs/Starlight), keep docs in the repo with PR review, build/preview/deploy in CI, version docs to match the product, and gate quality with link-checking + example-testing.

Setup guide for testing code examples in documentation CI — covers doctest, snippet extraction, execution sandboxing, and the failure-handling policy to ensure every published example actually runs.

Write composable Terraform/OpenTofu modules: single responsibility, typed variables with validation, documented outputs, for_each over count to avoid reorder churn, pinned provider requirements, and a working example.