20 skills (repositories by morluto) · sorted by popularity
Investigate performance bottlenecks in REA analysis workflows and improve caching, queries, or shared processing. Compare completed tasks before and after changes while preserving correct results, examined coverage, and access to supporting evidence.
Audit REA’s automated checks and test suites to find missed failures, outdated test data, and unnecessary work. Use reproducible experiments and timing measurements to assess fixes or efficiency changes while preserving checks that catch real defects.
Prepare REA changelogs and GitHub release notes from a fixed Git revision. Turn verified changes into clear user outcomes, preserve accurate contributor credit, and keep the release text aligned with Release Please, the automated release workflow.
Design or change REA investigation tools by defining responsibilities, inputs, results, and CLI or MCP interfaces. Produce a proposal that explains how Evidence records should be interpreted, compares the nearest existing alternative, and outlines verification.
Investigate shipped applications, binaries, packages, and firmware with REA to explain features, compare versions, or guide reconstruction. Use decompiled code and runtime observations where needed, keeping observed facts, inferred behavior, and unresolved questions clearly separated.
Use Jacobian’s typed operations when exact computation or structural analysis can help solve a mathematical problem.
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Review mathematical agent trajectories for evidence-backed Jacobian improvements; do not resume solving.
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Evaluate Jacobian reliability using recently resolved conjectures as held-out probes.
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Design, audit, or repair mathematical benchmark verifiers, submission contracts, and scoring.
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Audit a bounded mathematical slice for missing or unusable Jacobian capabilities, beyond a single-operation review.
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Use Jacobian's MCP operations for nontrivial mathematical computation, finite search, structural analysis, formal checking, probability, or optimization.
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Design or audit a Jacobian operation’s mathematical contract, boundedness, exact results, and composition.
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Investigate MCP tool availability, discovery, and selection, including controlled adoption evaluations.
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Author, package, validate, or run mathematical evaluations as Jacobian Harbor datasets.
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Diagnose malformed calls, retries, and unusable results after an agent selects an MCP tool.
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Extract reusable Jacobian capabilities from a mathematical solution corpus, rather than one agent trajectory.
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Investigate performance bottlenecks and validate optimizations without weakening retrieval quality or correctness.
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Create or revise repository-aware social preview images for GitHub, package pages, launch posts, and link cards. Use when an agent needs to inspect a project, sharpen its short positioning, generate a branded 2:1 raster preview, explore color variants, adapt a supplied visual reference without copying it, or validate and save a social-card image non-destructively.
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Use SmokingGun to find complexity candidates and organize imported optimization evidence.
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Activate a persistent visible-reasoning mode that requires detailed internalcot CLI notes before substantive tools and answers, throughout the conversation. Use only when the user explicitly invokes $internalcot, says "internalcot on", or asks to enable internalcot mode. Keep it active until the user explicitly turns it off. Do not trigger merely because a user asks to think carefully, reason deeply, or show work.
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