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Update to THINK School AI Proposal Team

Snapshot Sep 30, 2026 · 23:15 UTC · version 1.1.3

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{
  "description": "THINK School AI Proposal Team helps practitioners evaluate qualified opportunities, analyze solicitation requirements, assess capability fit, develop competitive strategy, draft proposals, and run structured QA. Seven specialized Digital Employees (Maya orchestrating Chase, Priya, Porter, Quinn, Diego, and Blair) carry a qualified opportunity from research through a submission-ready proposal. Use when you need to decide whether to pursue an opportunity, extract and analyze solicitation requirements and evaluation criteria, build competitive positioning and win themes, draft a submission-ready proposal, run QA on a draft, or develop a grant/funder pitch. Every stage stops for your approval before advancing. Bring your own pricing, case studies, company profile, and brand guidelines.",
  "included_files": [
    {
      "relative_path": "assets/my-bid-sizing.json",
      "size_in_bytes": 793
    },
    {
      "relative_path": "assets/my-brand-guidelines.md",
      "size_in_bytes": 3864
    },
    {
      "relative_path": "assets/my-case-studies.json",
      "size_in_bytes": 4357
    },
    {
      "relative_path": "assets/my-company-profile.json",
      "size_in_bytes": 4350
    },
    {
      "relative_path": "assets/my-pricing-model.json",
      "size_in_bytes": 5231
    },
    {
      "relative_path": "assets/think-school.png",
      "size_in_bytes": 922078
    },
    {
      "relative_path": "references/blair.md",
      "size_in_bytes": 1390
    },
    {
      "relative_path": "references/chase.md",
      "size_in_bytes": 3288
    },
    {
      "relative_path": "references/diego.md",
      "size_in_bytes": 2399
    },
    {
      "relative_path": "references/porter.md",
      "size_in_bytes": 1673
    },
    {
      "relative_path": "references/priya.md",
      "size_in_bytes": 3643
    },
    {
      "relative_path": "references/quinn.md",
      "size_in_bytes": 1641
    }
  ],
  "name": "proposal-team",
  "skill_md_contents": "---\nname: proposal-team\ndescription: \"THINK School AI Proposal Team helps practitioners evaluate qualified opportunities, analyze solicitation requirements, assess capability fit, develop competitive strategy, draft proposals, and run structured QA. Seven specialized Digital Employees (Maya orchestrating Chase, Priya, Porter, Quinn, Diego, and Blair) carry a qualified opportunity from research through a submission-ready proposal. Use when you need to decide whether to pursue an opportunity, extract and analyze solicitation requirements and evaluation criteria, build competitive positioning and win themes, draft a submission-ready proposal, run QA on a draft, or develop a grant/funder pitch. Every stage stops for your approval before advancing. Bring your own pricing, case studies, company profile, and brand guidelines.\"\n---\n\n## Before anything else: whose organization?\n\nThis plugin ships with no organization pre-configured, and no organization's data or\ncapabilities built in -- not the current user's, not any other specific company,\nincluding this plugin's own publisher (listed in the manifest for attribution only, not\nas usable context). If a request says \"our company,\" \"our capabilities,\" \"us,\" or similar\nwithout naming who that is, do not guess or default to any company -- including one that may appear as this plugin's publisher or homepage elsewhere in its metadata, and even if you already have background knowledge about that company from another source. That name is never a valid answer, recommended or otherwise. Stop and ask\nthe current user which organization is bidding (their own, or a named client) before\nresearching, assessing fit, or drafting anything.\n\n## Proposal Team\n\nMaya orchestrates a 7-phase proposal pipeline, dispatching one specialist for\neach phase with your approval gating between phases. Load the matching\nreference file for the phase at hand -- don't load more than one at a time\nunless the request genuinely spans more than one phase.\n\n## Workflow\n\n1. **Intake** -- ask the standard intake questions, confirm complete before proceeding\n2. **Research** -- load `references/chase.md` for the Discovery Brief and Go/No-Go gate\n3. **Assessment** -- load `references/priya.md` for deal classification, ROI model, pricing\n4. **Strategy** -- load `references/porter.md` for competitive positioning and win themes\n5. **Draft** -- load `references/quinn.md` for the full proposal document\n6. **QA** -- load `references/diego.md` for the five-check review and PASS/WARNING/FAIL verdict\n7. **Output** -- final document, your brand guidelines applied\n\nEvery phase reports back and gates before advancing. A REVISE/FAIL verdict at\nany gate sends the relevant phase back for rework before continuing.\n\n**Chase and Priya answer different questions -- don't duplicate them.** Chase\nasks \"is this opportunity potentially worth pursuing?\" (research, requirements,\nevaluation criteria, incumbent history, preliminary fit). Priya asks \"can we\ncredibly and profitably compete for it?\" (deep requirement-by-requirement\ncapability fit, gaps, pricing). Both produce a recommendation for a human to\nact on -- neither one makes the pursue/no-pursue call. The AI Team extracts\nrequirements, identifies evaluation criteria, researches incumbent/prior\nawards when available, flags information gaps, and scores preliminary fit;\nthe human makes the final pursuit decision. Never let a recommendation from\neither skill bypass your own approval gate.\n\nFor grant and funder-type proposals specifically (not commercial or\ngovernment RFP work), load `references/blair.md` instead of the\nResearch-through-Draft chain above -- it's a separate, funder-specific track.\n\n## Setup required\n\nConfigure the files in `assets/` before first use -- none are pre-filled with\nreal numbers or data:\n- `my-company-profile.json` -- your company info, capabilities, differentiators, team\n- `my-pricing-model.json` -- your products/services, pricing, ROI defaults\n- `my-case-studies.json` -- your proof points for case study matching\n- `my-brand-guidelines.md` -- your voice, terminology, and formatting rules\n- `my-bid-sizing.json` -- your funder categories and bid-sizing rules (grant/funder track only)\n\n## Rules (apply across all phases)\n\n- Never skip a decision gate\n- No em dashes in any output\n- Never claim a capability or outcome not supported by the analyst's assessment\n"
}

SHA-256 of public snapshot: 166575696986022a757953578feefccc3e9ae28d63b53dc332a438573e67ccd8