Distill Ml Knowledge

Distill ML Knowledge

Use this skill as the canonical Creator entry point for DisCo skill distillation. Convert a distillation anchor into a verified operating skill graph that a later Researcher can load. The four paper-aligned stages are scope, ground, construct, and verify. This skill does not execute the downstream research or software task in the current Creator session.

Identify The Anchor

Read task-and-construction-contract.md and create one anchor record before material exploration:

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# Distillation Anchor

- anchor kind: source | task
- anchor value:
  - source anchor: repository | paper | tutorial | dataset | benchmark | other
  - task anchor: `tau = (q, D, E, g)`
- source material: provided | discovered during grounding | mixed
- version/access/trust boundary:
- intended future use:
- unknowns and assumptions:

Use a source anchor for task-agnostic distillation. It may be a repository, paper, tutorial, dataset, benchmark, or comparable source and does not require a made-up downstream task. Use a task anchor for task-oriented distillation. The task-oriented D, E, and g values are blocking when routing or verification would change without them; ask for clarification before the affected action.

Scope, Ground, Construct, Verify

1. Scope the capabilities Q and define applicability, non-goals, candidate skill boundaries, graph entry points, and verification targets. For a task-agnostic anchor, begin with source understanding and capability identification. For a task-oriented anchor, begin with task decomposition and capability gap analysis.
2. Ground Q in retained evidence X. For task-agnostic distillation, extract knowledge from the source anchor. For task-oriented distillation, discover permitted source material for the capability gaps, then select and record evidence. Preserve provenance, versions, exclusions, conflicts, inaccessible material, and assumptions.
3. Construct a candidate graph G_tilde = (S_tilde, L_tilde). Use tool encapsulation and skill packaging for source-oriented work, or skill generation for task-oriented work. Each root and sub-skill needs a clear responsibility, progressive-disclosure route, evidence boundary, checks, and recovery behavior.
4. Verify the candidate graph with static, source-support, executable, graph/link, and applicable task-level or representative-use checks. Exercise failure recovery and repair affected skills, links, evidence mappings, or fixtures. The result is accepted graph G plus construction record R, or a candidate with explicit unverified blockers. Task-agnostic runs use source-supported representative workflows and do not invent a task-level outcome trial when no downstream task exists.

Creator Construction Strategy

After a lightweight scope/preflight, read construction-strategy-and-adequacy.md and record exactly one Creator construction strategy. This is implementation orchestration recorded in R, not a third distillation form:

• reuse-existing: invoke one adequate visible workflow or a bounded composition, preserving its verification, deployment, recovery, handoff, and specialized importer contract.
• direct: execute the four stages for the current anchor and produce the operating graph now.
• design-reusable: pass an evidence-backed recurring construction gap to design-meta-skill, which designs a future Creator workflow. It does not directly produce the current Researcher operating graph.

Record the layered routing fields below. Do not use the construction strategy to pretend that the anchor form is a task form:

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# Routing Record

- anchor kind: source | task
- distillation form: task-agnostic | task-oriented
- anchor `z`:
- scoped capabilities `Q`:
- required evidence and verification:
- construction strategy: direct | reuse-existing | design-reusable
- reuse mode: single | compose | not-applicable
- selected visible contracts:
- uncovered recurring construction gap:
- recurrence evidence:
- construction constraints and approval state:
- decision revision:

Apply auto by preferring an adequate existing workflow, then direct for a concrete task-conditioned need or design-reusable only for a verified recurring construction gap. A reusable preference tries reuse-existing first and must surface a conflict rather than silently falling back to a one-off direct run.

Handoffs And Deployment

For direct, read direct-construction-and-handoff.md and obtain approval of the exact construction specification after grounding. For reuse-existing, pass the anchor, Q, X, constraints, and ownership to the selected workflow without bypassing its verification or importer. For design-reusable, pass the complete routing handoff to ../design-meta-skill/SKILL.md; that skill must not repeat strategy selection.

After an accepted operating graph is verified, decide project or managed scope separately. Default task-bound or uncertain graphs to <project-dir>/.agents/skills/; use ~/.disco/agent/skills/ only for self-contained, provenance-backed graphs with representative reuse evidence. Keep every root and sub-skill in one scope, show exact destinations and collisions, obtain import approval, and invoke the selected specialized or generic locked importer once with all top-level roots.

Write researcher-handoff.md outside live skill roots with the anchor kind, distillation form, Q summary, X provenance scope, accepted or unverified G, R path, construction strategy, selected scope, exact imported paths, entry point, verification evidence, and unresolved limits. Do not load the resulting operating graph or execute the downstream task in this Creator run.