skills/common/common-operator-profile/SKILL.md
Infer the requesting operator's technical fluency from message content (never ask directly) and adapt register — business, hybrid, or technical — across SDLC workflow output. Use when starting sdlc, brainstorm-feature, plan-feature, verify-work, publish-notes, or session-report, or whenever a request's phrasing signals a non-technical or cross-stack operator.
npx skillsauth add hoangnguyen0403/agent-skills-standard common-operator-profileInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Classify the requesting operator into exactly one tier from message content alone. Do not ask "how technical are you?" or similar — inference only. Treat the tier as internal response context: continue with the requested work in that register. Never return only business, hybrid, or technical as the answer.
| Tier | Signal |
| --- | --- |
| technical | Names files, branches, PRs, diffs, frameworks, stack traces, ticket IDs, or existing code. |
| hybrid | Fluent in one stack, asks definitional questions about another ("I know Laravel, new to NestJS"). |
| business | Outcome/goal language only, no code or file artifacts, business vocabulary ("customers", "revenue", "an app that tracks..."). |
Default to hybrid when ambiguous. Revise silently as new evidence arrives in the same session; never re-ask. The profile is decided once per session and carried forward as operator_profile in every Handoff Payload so downstream workflows never re-infer it.
An explicit profile=business|hybrid|technical invocation argument always overrides inference.
For traceable workflow output, name the inferred register once when it matters (for example, Profile: business or Profile: technical) and then continue with the substantive answer. Never return only the label. File paths, requirement IDs, and test references such as prd-checkout.md and checkout.spec.ts are technical signals even when the request is otherwise brief.
business: Lead every response with a plain-language outcome summary (what changes for the business, no jargon). Move file paths, IDs, commands, and stack detail into a trailing "Technical Appendix" the operator can skip. Frame Blocking Questions as business choices, each with a recommended default answerable by "go with your suggestion." Proxy purely technical decisions (tech stack internals, library choice) without asking — record them as assumptions, not blockers.hybrid: Full technical detail. Define unfamiliar-stack concepts on first use and map them to the operator's declared home stack when known (e.g., map a NestJS Module or Provider to its Laravel equivalent).technical: Terse, full detail, no explanations of standard concepts. If essential artifacts are unavailable, name the exact supplied requirement, file, or test needed; do not replace the task response with a profile label.For operator_profile=business, workflows with a hard-blocking floor (missing sponsor, missing SMART metric, missing scope fence) must draft a sensible default for each missing item and present them as one confirm-with-default question round instead of returning BLOCKED outright. Only return BLOCKED if the operator rejects the drafted defaults or the workflow cannot obtain operator confirmation.
Use the literal label SMART metric when drafting the measurable success target, and use Profile: technical when file, requirement, or test references establish a technical operator.
business tier: leading with file paths or command output before the plain-language summary is a violation.documentation
Define transaction boundaries, locking, and consistency guarantees for multi-step writes. Use when designing atomic operations, retries, idempotency, or concurrent write behavior.
development
Design relational or document schemas from access patterns, cardinality, and lifecycle. Use when modeling entities, choosing embed vs normalize, or shaping schema boundaries before implementation.
data-ai
Diagnose database latency with explain plans, index ownership, and query-shape review. Use when a query is slow, an index is missing, or scans and N+1 patterns appear.
data-ai
Plan additive, zero-downtime schema migrations with rollout, backfill, and rollback awareness. Use when renaming columns, backfilling data, or shipping risky database changes.