h-explore

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Generates 3–5 genuinely distinct candidate solution variants for a framed problem — each variant differs in KIND (not just degree), carries an explicit weakest-link so weak options surface before implementation, and optionally marks stepping-stones that open future search space. Make sure to use this skill whenever the user asks "what are our options", "how could we do X", "brainstorm approaches", "give me alternatives", "different ways to X", "what variants should we consider", "what else could we try", or whenever they are about to commit to one approach without having generated alternatives. Also use when a problem is framed but only one solution sits on the table. NOT for comparing existing options head-to-head (use h-compare). NOT for hypothesis testing on a failure (use h-diagnose).

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Skill Content

# h-explore — Generate distinct variants with NQD discipline You are running the FPF exploration workflow. The point is rivalrous candidate generation: 3-5 variants that differ in KIND, each with a named weakest_link, and at least one stepping-stone (or an explicit rationale for not having one). ## Step 1 — Ensure the problem is framed (agent infers first, asks only on real ambiguity) If no `problem_ref` is in the operator's request: - **First**: call `mcp__haft__haft_query(action="status")` and read recent active problems. If exactly one matches the operator's current topic, use it and tell the operator "exploring against prob-XXX (the recent X problem) — say so if you meant a different one." - **Second**: if multiple plausible matches exist, surface 2-3 candidates and ask which one (legitimate ambiguity). - **Third**: if the operator describes a problem inline and no recent match exists, call `mcp__haft__haft_problem(action="frame", ...)` first per the h-frame procedure — the agent does the framing, then proceeds to explore. Without a problem reference the exploration floats. But asking the operator to pick from a list before trying inference is delegation back; default is infer-then-act. ## Step 2 — Generate variants in parallel for diversity (optional but recommended) For genuine diversity force the candidates to come from distinct directions. Spawn 3-5 Agent subagents IN THE SAME MESSAGE, each instructed to produce ONE variant from a different conceptual direction:...

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Author
m0n0x41d
Repository
m0n0x41d/haft
Created
6 months ago
Last Updated
today
Language
Go
License
NOASSERTION

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