How to use
- Copy the installation command and review the source package before installing it in your own agent environment.
- Check the source document for required tools, credentials and supported hosts.
- Describe your input and desired deliverable; review the output against the source material.
npx skills add https://github.com/novainsilico/jinko-skills --skill jinko-task-cmaesBefore you start
- Installation does not include a model subscription, API allowance or permission to access your files.
- Repository stars and installation counts describe activity, not an independent quality or security test.
Rendered from the source repository. Headings, examples, code, tables, links, and referenced images are preserved.
CMA-ES Calibration Task
Execute a confirmed calibration specification. Do not invent objectives, constraints, parameter priors, optimizer options, or acceptance criteria.
PREREQUISITE: This skill needs an initializedjinko-sdkconnection and an SDK satisfying itsmetadata.requires_sdkrange. Run thejinko-sdk-setupskill (../jinko-sdk-setup/SKILL.md) and proceed only once its check passes. If that skill is not found, install it fromnovainsilico/jinko-skills.
Inputs
Require:
- a model SID;
- parameter priors with physical bounds;
seed,thresholdWeightedScore,numberOfIterations, andpopulationSize;- at least one fitness source: calibration-ready data tables and/or an advanced
output set containing objectives;
- any protocol, simple output set, advanced output set, folder, and name needed
by the specification.
If quantitative evidence has not yet been converted into a calibration-ready table, use jinko-task-extract-data-table. Use jinko-data-table, jinko-output-set, jinko-model, and jinko-protocol only for their respective Jinkō object mechanics.
Workflow
- Resolve every input to its intended SID and snapshot. Present missing or
ambiguous inputs instead of guessing.
- Use
jinko-calibration-cmaesand its bundled creation script. Review its
dry-run output before applying it. The script owns parameter encoding, fitness-table eligibility, bound scaling, creation, and post-creation sanity; stop on an error and surface warnings.
- Return the created calibration SID, revision, snapshot, URL, and effective
options for confirmation.
- Use the lower-level run script to perform pre-launch sanity, launch, and wait
for a terminal state. Do not relaunch a terminal snapshot; create or update a configuration so the intended change has a new snapshot.
- Use the lower-level inspection interfaces to collect the final status,
stopping reason, performance, results summary, objective weights, and the patient sorted first by optimizationWeightedScore when available. Fetch per-patient scalars, timeseries, errors, or augmented data tables only when their required selectors are present in the result metadata.
Return
Return:
- calibration SID, revision, snapshot, and URL;
- effective input references, priors, and optimizer options;
- sanity warnings, terminal status, stopping reason, and performance;
- supported result payloads and best-patient identity, with the iteration and
scenario arm needed for subsequent result calls;
- a concise account of unavailable requested outputs.
Do not claim a separate run ID, convergence analysis, score-evolution curve, best-patient parameter values, parameter posterior, or simulation-vs-data plot unless the returned API payloads actually provide the required data.
