Audit a bounded mathematical slice for missing or unusable Jacobian capabilities, beyond a single-operation review.
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Author, package, validate, or run mathematical evaluations as Jacobian Harbor datasets.
中文简介正在准备中。当前显示原文说明。
查看安装方法安装前可以查看交给 AI 代理的指令内容。
Build a bounded mathematical experiment with a hidden, replayable verifier. Jacobian availability is an experimental condition, not a prerequisite for task admission. Task correctness depends on the submitted mathematics, not the agent's tool choices or transcript.
tests/fixtures/providers/.For submission design, mathematical predicates, scoring, or verifier repairs,
use verifier-evaluations. Ordinary packaging and execution do not require that
skill. A task's instruction and schema must expose its complete protocol while
keeping solutions, Oracle fixtures, verifier code, and host caches hidden.
Each task is a direct dataset child with one member record:
benchmarks/datasets/<dataset>/<task-id>/
benchmarks/datasets/<dataset>/members/<task-id>.toml
Use frozen offline inputs, pinned images and dependencies, and an explicit
execution profile. Verifier Dockerfiles build from tests/; avoid parent
COPY, host paths, floating tags, and symlinks. For the affected contract, use
benchmark contracts.
For local commands and planner selection, use the Harbor section of
CONTRIBUTING.md.
make harbor-plan BASE=origin/main
make harbor-prepare-task DATASET=<dataset> TASKS="<task-id>"
make harbor-validate-task DATASET=<dataset> TASKS="<task-id>"
Preparation formats selected task Python and refreshes contracts/checksums; validation runs the selected static, host, and Oracle checks without a model agent. Run the selected verifier's behavioral attacks when its contract changes. Report any deferred affected Oracle coverage.
For task-local support migrations, older contracts, checksum updates, or an intentional snapshot, read packaging details. Do not create a snapshot merely because a task contract changed.
Complete the requested task preparation and validation, repairing failures caused by the change within the authorized scope. Report the command, task digest, selected scope, Oracle result, and remaining evidence gaps. Distinguish local validation from a causal model comparison; model calls and external publication require the applicable user authorization.
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Audit a bounded mathematical slice for missing or unusable Jacobian capabilities, beyond a single-operation review.
中文简介正在准备中。当前显示原文说明。
Diagnose malformed calls, retries, and unusable results after an agent selects an MCP tool.
中文简介正在准备中。当前显示原文说明。
Design or audit a Jacobian operation’s mathematical contract, boundedness, exact results, and composition.
中文简介正在准备中。当前显示原文说明。
Extract reusable Jacobian capabilities from a mathematical solution corpus, rather than one agent trajectory.
中文简介正在准备中。当前显示原文说明。
Investigate MCP tool availability, discovery, and selection, including controlled adoption evaluations.
中文简介正在准备中。当前显示原文说明。
Use Jacobian's MCP operations for nontrivial mathematical computation, finite search, structural analysis, formal checking, probability, or optimization.
中文简介正在准备中。当前显示原文说明。