Match code investigation questions to the appropriate tldr command. Find ways to inspect files, function calls, branching, variable flow, and line dependencies, helping you explore a project or investigate a bug.
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Display a session dashboard showing Claude token usage, API costs, estimated savings from TLDR file summaries, cache reuse, and hook activity. Use it to compare compression results and check whether TLDR and automated hooks are running.
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Check whether infrastructure code actually runs when a user triggers it. Trace calls from hooks or commands through scripts and modules, verify registration and permissions, and test the complete path to uncover unreachable code.
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Find relevant code by describing what it does, even when identifiers use different words. The skill explains LEANN's meaning-based search, when to use exact text search instead, and how to rebuild the project's search index.
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Choose a mathematical approach for a problem you do not yet know how to model. Guided questions clarify change, uncertainty, optimization goals, and required precision, leading to a recommended framework, starting equations, tools, and related skills.
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Review progress while solving a math problem by organizing previous attempts, checking intermediate results, and assessing growing complexity. The skill recommends whether to continue, adjust the approach, switch strategies, or tackle a smaller problem first.
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Helps select graph algorithms for shortest paths, minimum spanning trees, network flow, and coloring. Provides decision guides and example commands for symbolic calculations and checking mathematical properties.
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Work through operator theory problems in functional analysis with structured steps for boundedness, adjoints, spectra, and compactness. Includes example commands for symbolic calculations and proof checks using SymPy and Z3.
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Plan solutions to modular arithmetic problems, which involve integer remainders. Choose methods for modular inverses, simultaneous congruences, powers, quadratic residues, and primitive roots, with example commands for symbolic calculations and checking mathematical claims.
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Plan solutions to Banach space problems in functional analysis. Work through completeness, meaning Cauchy sequences converge, and select major theorems to guide arguments about extending linear functionals, open mappings, and bounded operators.
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Study source coding, the information theory behind data compression. The skill guides problems involving Huffman codes, average code length, prefix-code constraints, arithmetic coding, and the tradeoff between compression rate and distortion, with calculation and proof command examples.
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Work through matrix eigenvalue problems, from the characteristic polynomial, whose roots give the eigenvalues, to finding eigenvectors. Follow a structured process to check the results and examine algebraic and geometric multiplicities.
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Work through linear algebra problems involving vector spaces, from checking subspaces and linear independence to finding bases, dimensions, and coordinate changes. The skill connects each task to symbolic calculation or proof scripts for checking the results.
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Work through predicate logic problems by examining quantifiers, which express “all” or “some,” organizing formulas, and choosing proof steps. The skill also guides resolution proofs and countermodels that show why an argument is invalid.
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Work through Lebesgue measure problems, which concern assigning sizes to sets. The skill organizes approaches to outer measure, measurability criteria, translation invariance, countable additivity, and approximation by compact or open sets, with supporting tool command examples.
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Work through measure theory problems involving sigma algebras, collections of sets closed under complements and countable unions. The skill outlines approaches to checking axioms, generating these collections, testing measurability, and studying products, with supporting tool commands.
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Choose numerical methods for approximating integrals based on the interval, function behavior, and number of dimensions. The skill guides SciPy calculations, error tolerance settings, and accuracy checks against known solutions or repeated calculations with tighter tolerances.
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Find numerical solutions where a function equals zero. The skill helps choose a method based on known intervals and available derivatives, then guides SciPy implementation, searches for multiple solutions, and checks accuracy and valid ranges.
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Work through convex optimization problems by checking convexity, putting objectives and constraints into a standard form, and choosing a solver. The skill provides SciPy examples and outlines checks for constraint satisfaction and mathematical conditions used to assess optimality.
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Work through optimization problems using gradients, which indicate how a function changes. The skill guides method selection, step size choices, and convergence checks, with SciPy examples for conjugate gradient and BFGS methods.
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Solve complex analysis problems by choosing residue calculations for different singularities, points where a function is not analytic. The skill covers limits, derivatives, Laurent series, and contour integrals using the residue theorem, with Sympy and Z3 command examples.
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Choose approaches to Hilbert space problems in functional analysis using orthogonal decomposition, projection, and representation theorems. The skill provides a decision tree and command examples for inner product calculations and proof tasks.
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Build a compact overview of an unfamiliar codebase with TLDR. Summarize its file tree, functions, classes, and calls between components, then highlight complex functions while reducing the amount of source text the agent needs to read.
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Choose approaches for prime number problems, including primality testing, factorization, and prime distribution. The skill outlines relevant algorithms and theorems, with commands for symbolic calculation and checking mathematical claims.
中文简介正在准备中。当前显示英语简介。