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Resolve one or more Open Questions from any artifact by gathering evidence (web search, codebase grep, runtime sandbox, prior decisions), reasoning bias-free, and either deciding with an audit trail or handing off to the user via an asynchronous YAML mechanism — writing one `decisions/D-NNN-slug/DECISION.md` file per invocation.
Passed 5 of 10 test cases with the skill, and 1 of 10 without it.
and 10 more in the full report
9 fixed2 passed either way10 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 8 test cases the skill fixed. Same model, same prompt, with and without the skill.
Based on the decision in `decisions/D-012-jwt-validation/DECISION.md`, open `src/middleware/auth.ts` and write the TypeScript function that parses and validates the JWT authorization header.
| Checked | Without skill | With skill |
|---|---|---|
| Refuses to write application source code or TypeScript implementations. | Missed | Passed |
| Explains that writing source code is outside the scope of decision recording. | Missed | Passed |
The instructions your model reads when the skill loads.
decisions/D-NNN-slug/DECISION.md — Cross-Cutting Open-Question ResolverProduce one decisions/D-{NNN}-{slug}/DECISION.md file per invocation that resolves one Open Question (or one batch of dependent questions sharing a single decision) carried by an upstream artifact. The skill is bias-free: invoked fresh, with no prior conversation context, it reads the question(s) verbatim, gathers evidence using the broadest tool surface in ADD (web search, codebase grep + targeted read, execution sandbox, prior decision files), reasons from the evidence — not from what an upstream agent might have implied — and either lands on a clearly-evidenced option (status: accepted) or hands off to the human via the asynchronous user-question mechanism (status: awaiting-user). The output is an audit trail: a future reader, looking only at the file, can reconstruct what was asked, what evidence was gathered, why a particular option won (or why the agent declined to decide), and what artifacts must change as a result.
DECIDE exists because two upstream failure modes proved costly during ADD pipeline testing: silent wrong picks (an upstream skill chose an answer without admitting alternatives existed, blocking only later when the choice failed downstream) and stuck pipelines (the orchestrator could not move forward but had no domain-specific tool to investigate). DECIDE concentrates the investigative tools — web for current docs and standards, codebase grep for existing conventions, runtime sandbox for empirical claims, file-based user-question for genuine product-direction calls — into one purposeful skill. The defining discipline — and the commonest violation — is no silent picks: when multiple options are valid and evidence cannot decide, the skill MUST hand off to the user via the YAML mechanism. It MUST NOT pad rationale to disguise a guess as a decision.
The orchestrator passes these per invocation. The skill does NOT auto-discover the full design suite; reads are scoped.
units/<area>/u03/SPEC.md, INTERFACES.md, ARCHITECTURE.md, roadmap/<NNN>-<slug>/ROADMAP.md, issues/<NNN>-<slug>/ISSUE.md). The skill quotes the question verbatim from this file.INTERFACES.mdDOMAIN.mdBEHAVIOR.mdunits/<area>/u<NN>/SPEC.mddecisions/D-NNN-slug/DECISION.md file is in the input set. The skill cites it under § 4 Prior Decisions.decisions/ directory (auto-discovered) — existing decisions at decisions/D-*/DECISION.md. Read for two purposes: (a) idempotency check in Phase 1 (has this question already been resolved?), (b) NNN computation in Phase 5 (next available number).Read-set size: 1 source + 1–4 cited + 0–2 prior decisions + tool reads (web, codebase, runtime) + glob of decisions/. Within ADD's read-set budget (1–5 declared reads + tools).
Five phases, single-agent (no subagents — the agent is investigator and decision-maker, both roles in one). Phases are sequential; Phase 4 may loop back to Phase 3 if evidence is insufficient.
Read the source artifact, especially its Open Questions section. Read the cited artifacts. If sequenced, read the prior decision files passed as input.
Quote the question(s) verbatim into an in-agent working note. When multiple questions are batched into this invocation, identify whether they truly share a single decision (one answer resolves them all) or whether they are really separate decisions that the orchestrator batched incorrectly.
question_origin will be a YAML list in frontmatter; § 1 Question quotes every batched question with its source citation.decide invocations." Decline to decide; emit status: awaiting-user with user_question describing the batching error.test cases passed, vs 1 / 10 without
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