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Agent skill

Root Finding

by parcadei in parcadei/Continuous-Claude-v3

Problem-solving strategies for root finding in numerical methods

MITAuto-check: notesResearch & Science

Install Root Finding

skills CLI
$ npx skills add parcadei/Continuous-Claude-v3 --skill root-finding -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install parcadei/Continuous-Claude-v3 root-finding --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/parcadei/Continuous-Claude-v3.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/math/numerical-methods/root-finding .claude/skills/root-finding && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
root-finding
GitHub stars
3.9k
Used in
2 other repos
Token cost
~886 tokens
SKILL.md length
395 words
Files
1
Skills in repo
141
Repo updated
First seen
Licence
MIT

At a glance

Problem-solving strategies for root finding in numerical methods

  • Works in 5 steps: Characterize the Problem → Method Selection → Implement Root Finding → …
  • Tasks that involve Math and symbolic computation
  • SKILL.md covers When to Use, Decision Tree, Tool Commands and Key Techniques, plus 1 more section
  • Calls uv

What it does

Root Finding is an agent skill from parcadei/Continuous-Claude-v3. Problem-solving strategies for root finding in numerical methods

Its SKILL.md is about 890 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Research & Science, covering Math and symbolic computation. The repository describes itself as: Context management for Claude Code. Hooks maintain state via ledgers and handoffs. MCP execution without context pollution. Agent orchestration with isolated context windows. The licence is MIT.

When your agent uses it

  • Tasks that involve Math and symbolic computation

Example prompts

  • “/root-finding”

Requirements

  • Python 3
  • Pre-approved tools (allowed-tools): Bash, Read

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Characterize the Problem
  2. Method Selection
  3. Implement Root Finding
  4. Handle Multiple Roots
  5. Verify Solutions

What it can do on your machine

Read from SKILL.md and the folder at commit d07ff4b. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Bash
    • Read

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • uv

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use uv, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Root Finding loads about 886 tokens when it runs. Until then it costs about 19 tokens; SKILL.md has 395 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~19
When it runs · the whole SKILL.md, loaded when a task matches
~886

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: Bash, Read

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from parcadei/Continuous-Claude-v3 at commit d07ff4b, republished under its MIT licence (© parcadei). 395 words, ~886 tokens.

Download SKILL.mdSave it as .claude/skills/root-finding/SKILL.md (or your agent's skills folder).
name
root-finding
description
Problem-solving strategies for root finding in numerical methods
allowed-tools
Bash, Read

Root Finding

When to Use

Use this skill when working on root-finding problems in numerical methods.

Decision Tree

  1. Characterize the Problem

    • Single root or multiple roots?
    • Bracketed (know interval containing root)?
    • Derivatives available?

  2. Method Selection

    SituationMethodImplementation
    Bracketed, no derivativesBisection, Brentscipy.optimize.brentq
    Derivatives availableNewton-Raphsonscipy.optimize.newton
    No derivativesSecant methodscipy.optimize.newton (no fprime)
    System of equationsscipy.optimize.fsolveRequires Jacobian ideally

  3. Implement Root Finding

    • scipy.optimize.brentq(f, a, b) - guaranteed convergence if bracketed
    • scipy.optimize.newton(f, x0, fprime=df) - quadratic convergence near root
    • For systems: scipy.optimize.fsolve(F, x0)

  4. Handle Multiple Roots

    • Deflation: divide out found roots
    • Multiple starting points
    • sympy_compute.py solve "f(x)" --var x for symbolic solutions

  5. Verify Solutions

    • Check |f(root)| < tolerance
    • Verify root is in expected domain
    • z3_solve.py prove "f(root) == 0"

Tool Commands

Scipy_Brentq
bash
uv run python -c "from scipy.optimize import brentq; root = brentq(lambda x: x**2 - 2, 0, 2); print('Root:', root)"
Scipy_Newton
bash
uv run python -c "from scipy.optimize import newton; root = newton(lambda x: x**2 - 2, 1.0, fprime=lambda x: 2*x); print('Root:', root)"
Sympy_Solve
bash
uv run python -m runtime.harness scripts/sympy_compute.py solve "x**3 - x - 1" --var x

Key Techniques

From indexed textbooks:

  • [Numerical analysis (Burden R.L., Fair... (Z-Library)] How accurate was his approximation? C H A P T E R 2 Solutions of Equations in One Variable 2. Survey of Methods and Software In this chapter we have considered the problem of solving the equation f (x) = 0, where f is a given continuous function.
  • [An Introduction to Numerical Analysis... (Z-Library)] Computational Solution of Nonlinear Operator Equations. Methods for Solving Systems of Nonlinear Equations. Society for Industrial and Applied Mathematics, Philadelphia.
  • [An Introduction to Numerical Analysis... (Z-Library)] General polynomial rootfinding methods There are a large number of rootfind ing algorithms designed especially for polynomials. Many of these are taken up in detail in the books Dejon and Henrici (1969), Henrici (1974, chap. There are far too many types of such methods to attempt to describe them all here.
  • [An Introduction to Numerical Analysis... (Z-Library)] J n Consider the product a 0 a 1 ••• am, where a 0 , a1, ••• , am are m + 1 num bers stored in a computer that uses n digit base fJ arithmetic. What is a rigorous bound for w? What is a statistical estimate for the size of w?
  • [An Introduction to Numerical Analysis... (Z-Library)] Discussion of the Literature There is a large literature on methods for calculating the roots of a single equation. See the books by Householder (1970), Ostrowski (1973), and Traub (1964) for a more extensive development than has been given here. Newton's method is one of the most widely used methods, and its development is due to many people.
Show full SKILL.md (9 more words)Show less

Cognitive Tools Reference

See .claude/skills/math-mode/SKILL.md for full tool documentation.

© parcadei, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .claude/skills/math/numerical-methods/root-finding of parcadei/Continuous-Claude-v3.

Open the folder on GitHubat commit d07ff4b

Used in 2 other repositories

We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in parcadei/Continuous-Claude-v3, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Root Finding next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Edu Solid Geometrywy51ai/edulab1.4k1 repos~1.1kAutomated safety check: PassApache-2.0
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Math Toolsananddtyagi/cc-marketplace6872 repos~1.3kAutomated safety check: PassNone

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Categories

Questions about Root Finding

What does Root Finding do?

Problem-solving strategies for root finding in numerical methods. Root Finding is an agent skill from parcadei/Continuous-Claude-v3.

When should I use Root Finding?

Root Finding fits situations like: tasks that involve Math and symbolic computation.

How do I install Root Finding in Claude Code?

Run `npx skills add parcadei/Continuous-Claude-v3 --skill root-finding -a claude-code`. Or copy the skill folder (.claude/skills/math/numerical-methods/root-finding in parcadei/Continuous-Claude-v3) into .claude/skills/root-finding in your project. Claude Code loads it when a task matches its description.

How do I install Root Finding in Codex?

Run `npx skills add parcadei/Continuous-Claude-v3 --skill root-finding -a codex`. Or copy the skill folder (.claude/skills/math/numerical-methods/root-finding in parcadei/Continuous-Claude-v3) into .agents/skills/root-finding in your project. Codex loads it when a task matches its description.

Can I use Root Finding in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add parcadei/Continuous-Claude-v3 --skill root-finding -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/root-finding, .gemini/skills/root-finding, .github/skills/root-finding and .opencode/skills/root-finding in your project.

What does Root Finding need to run?

Going by SKILL.md and its folder, Root Finding needs the command-line tools its instructions call (uv). Our summary lists: Python 3. Its frontmatter pre-approves these tools: Bash, Read.

Does Root Finding access the network?

SKILL.md contains no URLs. Its commands use uv, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Root Finding safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Root Finding use?

Root Finding is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Root Finding use?

About 886 tokens (SKILL.md is roughly 3.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Root Finding?

Skills that share tags, products or a category with Root Finding: Sympy (zLanqing/codex-claude-academic-skills, 4.6k stars), Edu Analytic Geometry (wy51ai/edulab, 1.4k stars), Edu Solid Geometry (wy51ai/edulab, 1.4k stars) and Math Modeling Competition Workflow (XiaoMaColtAI/math-modeling-skill, 1.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Root Finding?

parcadei (a GitHub user) maintains it in parcadei/Continuous-Claude-v3, which has 3,940 GitHub stars. The repository holds 141 skills in this directory. The repository was last updated on January 26, 2026.

Source: parcadei/Continuous-Claude-v3 on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.