Jurisdiction-aware legal document redlining agent: ingests customer-facing legal documents (NDAs, MSAs, DPAs, T&Cs, SOWs), segments them into clauses, rewrites each clause to align with internal policy positions and regional legal requirements, produces a fully redlined document plus a structured audit pack with change-by-change rationale and citations. Supports UK, EU, US, and custom jurisdictions. Use when user says "redline this contract", "review against our playbook", "localize this agreement", "adapt for EU", "adapt for UK", "jurisdiction review", "policy-aligned redline", "clause review", "contract redline", "playbook review", "mark up this agreement", "regional adaptation", "legal playbook", "NDA review", "MSA review", "DPA review", "T&Cs review", "standard positions review", "contract markup with audit trail", or needs jurisdiction-specific, policy-aligned contract redlining with full auditability.
Manage the Contoso RFP answer bank — search, add/update, sync Loopio exports, merge reviewer corrections. This is the retrieval substrate that every other rfp-* skill depends on.
Step 6 of the RFP Agent Swarm. Assembles the approved, gate-passed, reviewed responses into the buyer's required format (Word narrative, Excel questionnaire, PDF flattened, or portal CSV/JSON for Ariba / Coupa / Jaggaer), applies company branding, attaches the cover letter, and generates a companion analytics report covering match rate, confidence distribution, gate outcomes, effort metrics, and full response-level provenance. Use when user says "assemble the RFP response", "build the submission package", "generate RFP deliverable", "finalize RFP", "create analytics report", "package the RFP for submission", "produce the final deliverable", "compile RFP answers into the submission format", "generate the buyer-format response", "assemble the bid", or needs the approved responses turned into a branded, traceable submission package ready for the deal lead to submit.
Step 2 of the RFP Agent Swarm workflow. Produces a Go/No-Go recommendation MEMO for a freshly intaked RFP by running a weighted qualification scorecard across seven dimensions (KB match, technical fit, commercial fit, competitive position, strategic alignment, resource availability, deadline feasibility) and surfacing evidence, risks, and kill-criteria. The human ALWAYS makes the final bid/no-bid call — this skill only produces data and analysis. Use when the user says things like: - "should we bid on this" - "go/no-go analysis" - "fit score this RFP" - "qualify this RFP" - "bid decision" - "assess this RFP" - "should we respond" - "run fit assessment" - "score this opportunity" - "is this RFP worth pursuing" - "qualify [buyer name] RFP" - "build the Go/No-Go memo for leadership" Do NOT use for: parsing raw RFP documents (use rfp-intake), drafting the actual answers (use rfp-respond), running quality gates on drafts (use rfp-gates), assembling the final response document (use rfp-ass
Automated ingestion, parsing, and classification of incoming Request-for-Proposal (RFP), RFI, RFQ, tender, bid, and security-questionnaire documents. This skill extracts every question, classifies it by team (Security, Technical, Commercial, Company, General), detects mandatory vs optional items, extracts buyer metadata (deadline, submission format, evaluation criteria, page limits), and produces the structured task list that every downstream RFP skill consumes. Use when the user says any of: - "a new RFP came in, can you parse it" - "parse this RFP" - "intake this proposal" - "classify RFP questions" - "extract RFP questions from this document" - "log this RFP in our system" - "process this tender" - "ingest this bid document" - "break down this RFP by team" - "what's in this RFP, give me the summary" - "triage this security questionnaire" - "set up the task list for this bid" Do NOT use for: making the bid / no-bid decision (route to rfp-fit-assessment), drafting answer content (rf
Drafts first-pass answers to every RFP question using a strict retrieval-first pattern, routes questions to Security / Technical / Commercial teams in parallel, and stamps every response with a confidence tier and provenance before handing off to quality gates.
Step 5 of the RFP agent swarm. Surfaces only the flagged items that need human attention, captures every reviewer correction with a structured reason, and feeds the learning loop that improves the answer bank for future RFPs.
Batch-creates complete custom Cowork skill packages (SKILL.md plus optional references/, scripts/, assets/ folders) by first studying built-in skills as templates, then generating skills at a specified tier (Standard, Enhanced, Full Package) with rigorous quality controls, trigger-phrase density, cross-linked supporting files, and post-write verification. Use when the user asks to "create skills", "build a skill package", "generate custom skills", "make multiple skills", "bulk create skills", "spin up a skill package", "build a full skill", "create a tiered skill", "author a skill with references and scripts", "create skills in OneDrive", "skill factory", "batch skill creation", or describes a multi-skill authoring workflow with a quality bar. Do NOT use for single quick skill creation without supporting files — use the built-in `skills` skill for that. Do NOT use for editing, deleting, or auditing existing skills — use `skills` for lifecycle operations.