Tools · Strategy frameworks
Prioritization Matrices
Drop in a task list (and roles) — get a validated RACI plus impact/effort priority grids and a sequenced plan.
How it works
Corpus-grounded matrices with a code safety net: the model drafts the RACI assignments and the Complexity-Impact / Action-Priority quadrant placements grounded in the decision/management canon, then code VALIDATES the RACI rules (exactly one Accountable per task; RAPID mode: exactly-one-Decide, veto-count and R-capacity failure-mode checks for a single decision; flags zero/multiple owners, the every-role-Responsible smell, and over-consultation) and RE-DERIVES every quadrant from effort/impact — so placements are checked, not trusted. Returns a quick-wins-first sequenced plan. Complements the EOS Accountability Chart (MF-176): RACI is task/decision-level responsibility; EOS seats are org-structure roles.
You bring
{ tasks?: string[], roles?: string[], decision?, mode?: raci|prioritization|rapid|both }
You get
{ mode, raci?{roles, rows[], validation[], valid}, rapid?{decision, assignments[], validation, valid, failure_modes[]}, prioritization?{action_priority[], complexity_impact[], sequenced_actions[]}, grounded_in, provenance }
Use it for
- →Messy backlog with no owners: tasks + roles → a rule-validated RACI (every task gets exactly one Accountable) + a sequenced plan
- →Decide what to do first: drop initiatives in → quick-wins / major-projects / fill-ins / thankless quadrants with a so-what order
- →Audit an existing RACI: paste it in → the validator flags the no-owner, two-owner, and everyone-Responsible smells
Run it on your data
Call it on your own inputs — over the API, or hand it to your AI agent via MCP. Discovery is open; running it is metered.