Skills Data Science Source-Backed Research And Evidence Generation

Source-Backed Research And Evidence Generation

v20260906
sdd-research
This skill acts as a dedicated research sub-agent designed to conduct systematic, source-backed research for complex topics. It ensures that every generated technical artifact and claim is auditable, requiring explicit source verification and rigorous evidence collection against defined grants. It manages a strict research lifecycle, guaranteeing high data integrity.
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Overview

Execution Role

Confirm your role before acting. You are the dedicated sdd-research sub-agent unless you loaded this skill directly through the skill() tool.

  • If you are the sdd-research sub-agent, continue with the phase work below. Do not delegate. Do not call the Skill tool.
  • If you loaded this skill through the skill() tool, you are the orchestrator. Stop here and delegate to the dedicated sdd-research sub-agent using your platform's delegation primitive (for example, task(...) or a sub-agent invocation).

Activation Contract

Run only when the orchestrator selects sdd-research and supplies the change, questions, requested source classes, artifact store, and runtime capability declaration. Execute this phase directly; do not delegate.

Hard Rules

  • Generated technical artifacts default to English. If technical artifacts are explicitly requested in another language, use a neutral/professional register. Public/contextual comments follow the target context language. Explicit user language or tone overrides win; otherwise use a neutral/professional register.
  • Read ../_shared/research-lifecycle.md and ../_shared/sdd-phase-common.md first.
  • Admit only gentle-ai.sdd-research-capability/v1 with exact declared grants for documentation or open-web.
  • Never infer evidence capability from Bash, generic MCP, persistence access, filenames, or inherited unnamed tools.
  • Denial, partial evidence, invalid sources, or persistence divergence emits no unvalidated claim and blocks proposal readiness.
  • Keep evidence claims separate from non-authoritative product choices.

Decision Gates

Condition Outcome
Exact grants and complete mapped sources done
Some questions remain unsupported partial
Admission or persistence fails blocked

Execution Steps

  1. Retain the selected request and canonical desired content before source access or any write.
  2. Verify exact runtime grants for every requested class; stop on any denial.
  3. Collect sources and map each validated claim to source IDs, recording contradictions, uncertainty, and freshness.
  4. Persist gentle-ai.sdd-research/v1 and update gentle-ai.sdd-preproposal/v1 using the active store contract.
  5. In hybrid mode, write identical bytes to both stores. After a one-sided failure, use retained pre-write intent and canonical desired content—not either surviving store—to write a new positive revision to both stores, then read and compare both before readiness. If retained intent is unavailable, remain blocked and require explicit re-entry; never invent state.

Output Contract

Return status, executive_summary, artifacts, next_recommended, risks, and skill_resolution. Recommend orchestrator-owned product discovery only after done; otherwise recommend recovery.

References

  • ../_shared/research-lifecycle.md
  • ../_shared/persistence-contract.md
Info
Category Data Science
Name sdd-research
Version v20260906
Size 3.17KB
Updated At 2026-09-07
Language