executing-plans
executing-plans
Use when executing an implementation plan in the current session as the implementer yourself — your human partner chose inline execution, or no subagent tool is available
simulation-need-discoveryUse when handling simulation requirement docs, 任务书/specs, client/lab/customer asks, vague modeling requests, paid gigs, or before costly full solves, long runs, sweeps, optimization, calibration, and coupled simulations where the decision, physical model, assumptions, validation evidence, or deliverable must be clear before execution.
Independent GitHub snapshot · Automated classification · Original documentation governs
Use this skill before doing simulation work when the request may not yet be the real spec. The stated ask is evidence, not a command to blindly implement.
Your job is to identify the real decision, the evidence needed to support that decision, the smallest acceptable deliverable, and the assumptions that must be visible before modeling starts.
This skill is intentionally lightweight. It should guide judgment without forcing a fixed folder layout, filename scheme, solver, geometry package, or modeling recipe.
Do not jump straight from request to model.
First answer:
If the answer is already clear, proceed. If not, ask only the highest-value missing questions or propose explicit assumptions.
Before a costly full solve, long run, sweep, optimization, calibration, or multi-physics escalation, establish a compact execution contract:
Present these six items as a compact contract before asking the decisive question or starting execution. Mark each unresolved item as an assumption or blocked item so the user can see what is ready and what is not.
If one P0/P1 ambiguity would change the physical model, ask at most one decisive question. List every other gap as an assumption or blocked contract item, not as another question; the response may contain only one user-answerable question. Otherwise proceed with visible assumptions. Run the smallest case that can test setup, sign/convention, boundary behavior, and expected output before launching the full job. Start the full execution only after that smoke produces the expected evidence, or record why the gate is being bypassed and what extra risk remains.
For a comparison, sweep, or redesign, add one controlled-comparison line: baseline, hypothesis, intended change, invariants, leading metric, and rejection condition. Prefer one causal change per variant. If several changes are inseparable, stage them or label the result as a bundled comparison rather than attributing the outcome to one factor.
Use this skill for:
Do not use this skill as a replacement for solver execution. It routes work; it does not contain COMSOL, Fluent, Mechanical, Abaqus, OpenFOAM, or electronics solver mechanics.
Read the request as a bundle of clues:
Prefer a short restatement of the real decision and the minimum useful deliverable before proposing implementation.
Before modeling, make the deliverable concrete enough to prevent drift.
Clarify:
Keep this flexible. Do not impose exact folders or filenames unless the user, repo, or product workflow already has a convention.
Make a compact inventory:
Avoid treating every missing detail as equally important.
Rank missing information by how much it can change the plan:
Outside the Solver Launch Gate, ask only the highest-value missing questions, usually no more than three to five at once. At the gate, keep the stricter one-question limit above. If momentum matters, propose defaults and continue with visible caveats.
Use the cheapest artifact that answers the current uncertainty:
Do not launch a heavy solver just to discover that the geometry, objective, or deliverable was misunderstood.
For non-trivial simulation work, use progressive fidelity as the default operating loop:
Do not add detailed geometry, secondary physics, coupling, sweeps, optimization, calibration, or polished automation until the current layer has evidence that it runs and supports the scoped claim. If a layer must be skipped because the decision, data, or stakeholder requirement demands it, document the bypass reason and the extra risk it creates.
Keep each layer solver-neutral in the plan: name the uncertainty it reduces, the artifact it will export, and the check that allows escalation.
Use geometry-preview for topology-aware geometry preflight before heavy solver
work when geometry matters:
Escalate to solver-specific skills only when the uncertainty is solver-specific:
This skill should not duplicate solver recipes.
When the request is too broad, convert it into a layered path:
Use pushback when the stated request asks for full fidelity, full optimization, paper-quality proof, or all-physics coupling without enough inputs, time, or validation data.
Good pushback names the risk, offers a cheaper artifact, and states both what that artifact would and would not prove.
Before handing over results, check that the artifact supports the agreed claim:
If validation is weak, say so plainly and frame the result as exploratory, directional, or a first-pass model.
Prefer targeted questions over intake forms.
At the Solver Launch Gate, ask at most the single decisive question identified above; represent the remaining unknowns in the compact contract instead.
Examples: ask what decision the result supports, what would make the recipient accept the answer, whether the deliverable is a model, figure, report, or workflow, which inputs are fixed, what reference data exists, and whether the main risk is geometry, physics fidelity, or delivery speed.
If the user is unavailable, continue with explicit assumptions and identify the assumption most worth revisiting.
Do not claim:
It is fine to produce exploratory artifacts. Label them honestly.
When useful, summarize the discovered scope in this shape:
Use the template only when it helps. For simple requests, a short paragraph is better than ceremony.