decide
Which models fit this job? Returns answer, ranked results, may_qualify, reading and recovery hints, decision_id and snapshot. Never add a gate or constraint the user didn't state. Relax only constraints the user stated, one at a time, and say what was relaxed and why. Prefer the answer's own relax suggestions. A tie stays a tie. Don't promote a member by knowledge from outside the response. Cite only evidence in the response. Never add benchmark figures from memory. Tied or partial answer: report the tie and caveats, pick no member; a null answer names no pick and says what's missing. A null cost is unknown. Never show it as $0.00 or "free". One vocabulary lookup per unknown facet, then decide. Read next before another call. Size task_tokens from the user's own task, and say what you assumed. Don't copy the guide's example sizes. Template weights are examples, not requirements. If the evidence basis or board does not match the task, say so: Arena web-dev evidence does not establish chat quality. p_best is the probability of ranking best under the Spec and evidence uncertainty, not the probability of matching the user's task or satisfying its requirements. Read reading when present. Present answer.kind=tied among all answer.members, including with_estate; tie-breakers are conditional. State requirements in reading.not_applied or error.issues that were not applied, including requirements removed after a rejected call. A retry does not verify them. Report estimates as estimates: fits_hardware membership is not measured fit for a specific quantization and context workload. Follow reading.do_not_claim. Never claim a rank the response does not show. Present summary_for_user to the user unchanged and keep every must_mention item. When next_move is present, offer it instead of a pick. Needs an API key (Authorization: Bearer). Costs 1 or 2 credits a call; a credit costs $0.0053–$0.02 depending on the plan or pack (https://modelspec.dev/pricing/). Not a router: call it once per job or role, not per request, then route among the models it recommends. Proxies POST https://api.modelspec.dev/v1/decide. Call decide early with a template-based Spec; refine from reading and recovery hints. Put Musts in where: these gates exclude. Put Prefers in optimize.weights: weights rank and never exclude. Unknown values go to may_qualify. Pin snapshot for reproducibility. MCP decide returns a bounded answer of at most 16 KB, summary included. Drill down with evidence_for. Complete rows need fields:null; explanation.fetch names what was removed and how to fetch it. With explain unset or "none": explain=none, limit=10, fields model_rank, cost_per_task, estimates, p_best. summary or full also sends contributions and evidence. omitted counts removed records; explain=none does not compute eliminations. explicit fields, including null, is sent as given. Over 16 KB the body is a trimmed notice and explanation.fetch says how to resend. decision_id is a citation, not a stored lookup. task free text is rejected; where is an array. Call shape, examples, recovery and budgets: https://modelspec.dev/agents.md. Null means not researched or not published, never a guess. Every sourced value on a card carries a URL and a read date. This tool returns the origin's JSON plus the origin URL; it does not invent fields. Example. Answer: status partial, answer.kind tied (a/x, b/y), next_move.kind decide_by_testing. Right report: summary_for_user verbatim, each must_mention item, then next_move.steps for its candidates. Wrong: "Start with a/x", a shortlist, or a ranked table.
Input Schema
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