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by shingo imotasimota/agent-skills85 stars
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Converting technical knowledge into durable learning documents and publishable articles. Use for diff-based teaching, decision records, onboarding, note/Zenn/Qiita/dev.to posts, article series, retrospectives, and cross-platform repurposing.

Use this Skill: https://skilld.dev/gh/simota/agent-skills/tome

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referencecoding-kata.md

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Coding Kata Reference

Purpose: Design deliberate-practice coding exercises in the kata tradition (Dave Thomas, "Code Kata," 2005). Katas are short, repeatable problems practiced under constraints to build technique — not to ship features. Repetition with reflection beats breadth.

Scope Boundary

  • tome kata (this command): deliberate-practice exercise spec. Includes constraints, difficulty progression, comparison-target solutions, and facilitator notes.
  • tome worked: shows the expert solution with reasoning. Kata withholds the solution; the learner produces it.
  • tome learn (default): explanation-oriented learning doc grounded in a real diff. Kata is practice-oriented and synthetic.
  • tome onboard: comprehensive material for new joiners. Kata is narrower and skill-targeted.
  • tome record: ADR. Kata teaches a technique; ADR records a decision.
  • vs Scribe (elsewhere): Scribe writes specs/PRDs. Kata is exercise material.
  • vs Quill (elsewhere): Quill produces inline code documentation. Kata is a standalone exercise document.
  • vs Stage (elsewhere): Stage builds slide presentations. Kata is for hands-on practice, not presentation.

Workflow

SELECT       →  pick a problem small enough to attempt in 30-60 min
             →  confirm it isolates a single technique (parsing, recursion, modeling, etc.)

CONSTRAIN    →  design 1-3 constraints (time / language / paradigm / no-loops / TDD-only)
             →  constraints are the practice — without them it is just an exercise

PROGRESS     →  define 3 difficulty tiers (Bronze / Silver / Gold)
             →  each tier adds a constraint or removes a hint

COMPARE      →  prepare 2+ reference solutions (idiomatic, contrasting paradigm)
             →  shown ONLY after the learner submits an attempt

FACILITATE   →  write notes for solo, pair, and group runs
             →  include retrospective prompts and stuck-state hints

Constraint Catalog

Constraint Mechanism Trains
Time-box 30 / 45 / 60 minutes hard stop Decisive simplification
Language switch Solve in unfamiliar language Concept vs syntax separation
No-loops Recursion / map-reduce only Functional thinking
TDD-only Red-green-refactor strict Test-first discipline
No mouse Keyboard-only navigation Tooling fluency
No if Polymorphism / table-driven Branching alternatives
Pair-driver Driver implements; navigator reads spec only Communication
Mute pair Pair writes only — no speech Code-as-message clarity

Pick constraints that pressure the technique you want to train. Stacking 3+ constraints usually breaks the kata; cap at 2 unless explicit.

Tier Structure (Bronze / Silver / Gold)

Tier Constraint count Hint level Comparison target
Bronze 0-1 Step-by-step approach hint provided One canonical solution shared after attempt
Silver 1-2 Approach-only hint Two contrasting solutions shared after attempt
Gold 2-3 Problem statement only Three+ solutions including expert anti-pattern note

Gate progression on completion within time-box, not subjective satisfaction. Repeating the same tier with a fresh constraint is normal practice.

Common Katas (Reference)

Kata Trains Typical constraints
FizzBuzz Branching / table-driven thinking No if, table-driven
Roman Numerals Lookup vs algorithm trade-offs TDD-only, time-box
Bowling Game State machine, sequence parsing No mutable state
Gilded Rose Refactoring under tests Cannot rewrite from scratch
Tennis Game Domain modeling, naming No primitives in interface
Mars Rover Command parser, state Functional only
Bank OCR Parsing, ambiguity handling Streaming I/O only
Diamond Symmetry, generative thinking TDD with property tests

Cite the source kata when adapting; do not present folklore as new.

Platform Landscape (2026)

Match the platform to the practice goal, not vice versa. As of 2026-05:

Platform 2026 strength Best for
Exercism 82 language tracks with mentored feedback (free, volunteer mentors) Language fluency, paradigm-shift katas, getting external feedback
Codewars 67 language challenges, gamified; 2026 roadmap announced platform upgrades and AI partnerships Daily repetition, ranking-driven practice, language switching
LeetCode / HackerRank Interview-style problems Interview prep — not deliberate-practice katas
Frontend Mentor Frontend project briefs (HTML/CSS/JS/React) UI kata, visual-design constraints
Scrimba Practice-while-learning, integrated editor Tutorial-driven warmup before kata work

[Source: scrimba.com/articles — Best Coding Practice Platforms 2026; algocademy.com — 7 Best Coding Kata Sites]

Trend signal: consistency over intensity remains the dominant 2026 advice — daily short sessions outperform weekly marathons. Pair facilitation guidance with a platform that supports the constraint you want to train (e.g., Exercism's mentor channel for "code-as-message" katas where written explanation is part of the practice).

Pair vs Solo vs Group

Mode Strength Watch out for
Solo Honest self-confrontation, deep reflection No external check on rationalization
Pair (driver/navigator) Communication forced, double-loop learning Dominant partner monopolizes keyboard
Mob (3-5) Shared mental model, language exchange Slow; energy drain past 90 min
Code-review kata Reading skill, articulation of bad smells Requires curated bad code; production code rarely fits

Facilitator Notes

  • Time-box is non-negotiable. Stop on the buzzer regardless of completion. Reflection requires uncompleted attempts more than complete ones.
  • Reflection prompts beat retrospective venting. Use: "What surprised you? What did the constraint force? What would change the second pass?"
  • Reveal reference solutions only after attempts. Prematurely showing comparison targets converts a kata into a worked example.
  • Encourage throwing the code away. Persistence-of-output is a feature anti-pattern; the technique is internalized in the hands and head.

Anti-Patterns

  • Kata without constraints — degenerates into a regular coding problem; deliberate-practice value drops to near zero.
  • Constraint stacking 3+ at Bronze tier — overwhelming; learners attribute failure to the kata, not the technique.
  • Skipping comparison-target solutions — learners cannot calibrate their solution against the technique being trained.
  • Showing solutions before attempts — converts kata to worked example; recall-strengthening effect is lost.
  • Reusing katas without rotation — same problem, same insight, no growth. Rotate techniques across sessions.
  • Production code masquerading as kata — too large, too entangled with codebase context, no clean technique isolation.
  • No facilitator notes — pair/group modes go off the rails without dominance and time-box guardrails.
  • "Winner" framing in group katas — ranking individual solutions destroys the learning culture katas depend on.
  • Treating completion as the goal — completion is incidental; the constraint-induced struggle is the practice.

Handoff

  • To Scribe: when a kata reveals a technique worth promoting to a team coding standard or spec rule.
  • To Quill: when kata-discovered patterns deserve inline annotation in the codebase.
  • To Stage: when running a kata-night talk — Stage handles pacing, slide-by-slide reveals, and speaker notes.
  • To Saga: when a kata-derived insight should become a customer-story narrative.
  • To Tome worked: pair this kata with a worked example of the canonical solution for learners who get stuck repeatedly.

Source: SKILL.md on GitHub

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    The 'tome' skill is a technical documentation and article authoring tool designed to convert git changes and raw source material into structured learning assets. It incorporates robust safety standards, such as a strict 'Documents only' policy and mandatory masking of sensitive information like credentials and client details. While the skill processes external data, it includes explicit mechanisms to prevent the execution of untrusted instructions, ensuring a secure environment for technical writing.

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