From brain
Use when a task asks to run calculations, simulations, model training, searches, benchmarks, optimizations, workflows, agents, pipelines, or other tool-heavy execution before the scientific question and interpretation boundary are clear.
How this skill is triggered — by the user, by Claude, or both
Slash command
/brain:think-before-you-calculateThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Use this skill as the pre-execution brake. It keeps calculations, tools, benchmarks, and workflows from silently defining the question.
Use this skill as the pre-execution brake. It keeps calculations, tools, benchmarks, and workflows from silently defining the question.
Core principle: run tools strongly, but never let tool output become a conclusion without object, proxy, evidence, failure, and responsibility boundaries.
NO EXECUTION-BASED CONCLUSION WITHOUT A PRE-CALC AUDIT
You may run an exploratory calculation with missing fields, but you must label it exploratory and must not turn the result into scientific understanding.
Weak models must use these meanings, not guess.
| Term | Meaning |
|---|---|
calc | Any calculation, simulation, derivation, ML training, benchmark, search, workflow, pipeline, or agent tool execution. |
object | The real thing, phenomenon, mechanism, system, or code state the work is about. It is not automatically a dataset, metric, or output. |
boundary | The scope where the result is meant to hold: data split, approximation, environment, assumptions, system limits, or use case. |
representation | How the object enters the system: coordinates, graph, Hamiltonian, tensor, prompt, AST, trace, embedding, schema, etc. |
proxy | A measurable or optimizable substitute for the real object or goal: metric, loss, label, benchmark, generated candidate, workflow success. |
evidence | What the calculation or tool output actually supports. |
failure path | How the result could fail or be falsified: distribution shift, broken approximation, missing variable, invalid workflow, bad tool call. |
responsibility | Who owns setup, interpretation, failure analysis, and final claim. |
productive function | The real narrow value of the tool: speed, scale, reproducibility, comparison, automation, cost reduction, candidate generation. |
narrow claim | The strongest claim the evidence supports without inflation. |
Before execution or conclusion, fill this. Use Unknown rather than inventing.
Object:
Boundary:
Representation:
Proxy / Optimization Target:
Evidence Expected:
Failure Path:
Responsibility:
Productive Function:
Narrow Claim This Could Support:
If any gate fails, label the run exploratory or narrow the claim.
No object -> no object-level claim.
No boundary -> no generalization claim.
No proxy explanation -> no claim beyond proxy success.
No failure path -> no strong success claim.
No responsibility owner -> no autonomy/safety/reliability claim.
No productive function check -> critique may become over-dismissal.
If the user only wants execution, keep the audit to 3-8 lines, then proceed.
After execution, write conclusions in this form:
The result supports [narrow claim] under [boundary].
It does not establish [inflated claim].
Missing evidence: [gap].
Failure path: [failure condition or Unknown].
Responsibility owner: [owner or Unknown].
Productive function: [real value].
Stop and audit when:
Use a more specific skill when the task is not just pre-execution:
epistemic-systems-audit for papers, AI4S, benchmark claims, scientific understanding claims, and claim repair.whole-object-responsibility for agent OS, workflow systems, infrastructure, HPC, distributed systems, protocol failure, and division-of-labor responsibility.First make the calculation answerable. Then calculate.
Creates, edits, and optimizes skills for Claude Code, including drafting, evaluating with test prompts, iterating on performance, and improving skill descriptions for better triggering accuracy.
npx claudepluginhub ansatzx/cyberbrain --plugin brain