Implementation

Verification-driven coding with tight feedback loops. Distilled from 21,321 tracked operations across 64+ projects, 612 debugging sessions, and 2,476 conversation histories. These are the patterns that consistently ship working code.

Core insight: Verify in tight loops, roughly every 2-3 edits. 73% of fixes go unverified across the dataset, which is the single biggest quality gap. Sessions that maintain a tight verify cadence avoid the debugging spirals that the rest of this skill is designed to prevent.

How to read this skill: the loop and the heuristics below are calibrated for non-trivial implementation work. Trivial fixes (config, typo, single-line) shouldn't drag through five phases. Use judgment, scale planning to scope, and skip what doesn't apply. The Code Discipline section is principles that bias toward caution; for one-line changes, just make the change.

The Loop

Most implementation work flows through the same shape, regardless of scale:

digraph implement {
    rankdir=LR;
    node [shape=box];

    "ORIENT" [style=filled, fillcolor="#e8e8ff"];
    "PLAN" [style=filled, fillcolor="#fff8e0"];
    "IMPLEMENT" [style=filled, fillcolor="#ffe8e8"];
    "VERIFY" [style=filled, fillcolor="#e8ffe8"];
    "COMMIT" [style=filled, fillcolor="#e8e8ff"];

    "ORIENT" -> "PLAN";
    "PLAN" -> "IMPLEMENT";
    "IMPLEMENT" -> "VERIFY";
    "VERIFY" -> "IMPLEMENT" [label="fix", style=dashed];
    "VERIFY" -> "COMMIT" [label="pass"];
    "COMMIT" -> "IMPLEMENT" [label="next chunk", style=dashed];
}

ORIENT. Read existing code before touching anything. Grep → Read → Read is the dominant opening across the dataset. Sessions that read 10+ files before the first edit require fewer fix iterations downstream. Blind changes are the most expensive way to start.

PLAN. Scale-dependent (see below). Trivial fixes don't need a plan; features benefit from a task list; epics earn a research swarm. The decision is "what's proportional," not "always plan."

IMPLEMENT. Work in batches of roughly 2-3 edits, then verify. Follow the dependency chain. Edit existing files 9:1 over creating new ones; that's the observed ratio in successful sessions. Fix errors as they surface; accumulating them creates cascade-debugging.

VERIFY. Typecheck is the primary gate, fast and cheap; run it between batches. Tests fit naturally after feature-complete. Full suite before commit.

COMMIT. Atomic chunks, committed as you go. Verify, stage specific files, commit, loop back to the next chunk. Many small commits per session is the pattern that consistently outperforms one mega-commit at the end. See Commit Cadence below for message anatomy.

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Code Discipline

Principles that shape how you move through the loop, not steps to execute. Adapted from Karpathy's observations on LLM coding pitfalls: models "make wrong assumptions on your behalf and just run along with them without checking ... really like to overcomplicate code and APIs, bloat abstractions ... implement a bloated construction over 1000 lines when 100 would do."

These principles bias toward caution because that's where models drift. For trivial fixes, the calculus inverts; apply judgment, not the full discipline.

Think before coding

Don't assume. Don't hide confusion. Surface tradeoffs.

ORIENT (read the code) is the prerequisite. This principle is what to do with what you find: name the gaps, don't paper over them.

Simplicity first

Minimum code that solves the problem. Nothing speculative.

The test: would a senior engineer call this overcomplicated? If yes, simplify.

Surgical changes

Touch only what you must. Clean up only your own mess.

The test: every changed line should trace directly to the user's request.

Goal-driven execution

Define verifiable success. Loop until it passes.

For multi-step work, state the plan with verification per step:

1. [Step] → verify: [check]
2. [Step] → verify: [check]
3. [Step] → verify: [check]

Strong success criteria let you loop independently. Weak criteria require constant clarification.

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Scale Selection

Strategy changes dramatically based on scope. Pick the right weight class:

Skip planning when: Scope is clear, single-file change, fix describable in one sentence.

Plan when: Multiple files, unfamiliar code, uncertain approach.

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Dependency Chain

Build things in this order. Validated across fullstack, Rust, and monorepo projects:

Types/Models -> Backend Logic -> API Routes -> Frontend Types -> Hooks/Client -> UI Components -> Tests

Fullstack (Python + TypeScript):

1. Database model + migration
2. Service/business logic layer
3. API routes (FastAPI or tRPC)
4. Frontend API client
5. React hooks wrapping API calls
6. UI components consuming hooks
7. Lint -> typecheck -> test -> commit

Rust:

1. Error types (thiserror enum with #[from])
2. Type definitions (structs, enums)
3. Core logic (impl blocks)
4. Module wiring (mod.rs re-exports)
5. cargo check -> cargo clippy -> cargo test

Key finding: Database migrations are written AFTER the code that needs them. Frontend drives backend changes as often as the reverse.

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Verification Cadence

The single most impactful practice in the dataset. Tight loops here make the rest of the skill mostly unnecessary; loose loops make every other guideline harder to follow.

The edit-verify-fix cycle

The pattern that consistently produces clean sessions: ~3 changes → verify → 1 fix. Sweet spot, not a hard ratio. Sometimes one edit warrants its own verify, sometimes five edits group cleanly.

The pattern that produces debugging spirals: 2 changes → typecheck → 15 cascading fixes. Prevent type cascades by grepping consumers before modifying shared types; once the cascade starts, separate fix domains (see Error Recovery).

Combined gates save time: turbo lint:fix typecheck --filter=pkg runs both in one shot. Scope verification to affected packages, never the full monorepo.

Practical tips:

• Run lint:fix BEFORE lint check to reduce iterations
• cargo check over cargo build (2-3x faster, same error detection)
• Truncate verbose output: 2>&1 | tail -20
• Wrap tests with timeout: timeout 120 uv run pytest

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Decision Trees

Read vs Edit

Familiar file you edited this session?
  Yes -> Edit directly (verify after)
  No  -> Read it this session?
    Yes -> Edit
    No  -> Read first (79% of quick fixes start with reading)

Subagents vs Direct Work

Self-contained with a clear deliverable?
  Yes -> Produces verbose output (tests, logs, research)?
    Yes -> Subagent (keeps context clean)
    No  -> Need frequent back-and-forth?
      Yes -> Direct
      No  -> Subagent
  No -> Direct (iterative refinement needs shared context)

Refactoring Approach

Can changes be made incrementally?
  Yes -> Move first, THEN consolidate (separate commits)
        New code alongside old, remove old only after tests pass
  No  -> Analysis phase first (parallel review agents)
        Gap analysis: old vs new function-by-function
        Implement gaps as focused tasks

Bug Fix vs Feature vs Refactor

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Error Recovery

65% of debugging sessions resolve in 1-2 iterations. The remaining 35% risk spiraling into 6+. The patterns below are calibrated to keep you in the first bucket.

Quick resolution

• Read the relevant code first (79% success correlation in the dataset)
• Form an explicit hypothesis: "the issue is X because Y"
• Make one targeted fix
• Verify the fix actually worked before moving on

Spiral prevention

• Separate error domains. Fix all type errors before chasing test failures; interleaving the two is how cascades compound.
• 3-strike heuristic. Three failed attempts on the same error is the signal to change approach entirely or escalate, not to try variation #4.
• Cascade depth > 3. Pause, enumerate all remaining issues, then fix in dependency order rather than reactive whack-a-mole.
• Context rot. After ~15-20 iterations, /clear and start fresh. A clean session with a better prompt usually outperforms accumulated corrections.

Two-correction rule

Correcting the same issue twice is the signal to /clear and restart. Context noise compounds faster than fixes resolve it.

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Commit Cadence

Commit each logical chunk as it lands and verifies. Many small commits per session is the norm, never accumulate hours of unrelated work into one mega-commit. The COMMIT step loops back to IMPLEMENT for the next chunk.

When to commit

If a reviewer would want it as a separate diff, it's a separate commit.

Mirror local style

Before the first commit in any repo, run git log -10 --oneline and mirror the pattern. Mirror format, not quality, terse history doesn't lower your bar. Default to Conventional Commits when no pattern exists.

Conventional Commit types: feat (capability), fix (bug), refactor (no behavior change), perf, test, docs, style (formatting only), chore (tooling/deps), build, ci. Scope is optional but encouraged when the change is localized.

Message anatomy

Subject: imperative mood, ≤76 chars, no trailing period, no filenames. "Fix null deref in token refresh" beats "Fix bug." For Conventional Commits, no emoji in the subject, it breaks parsers.

Body (always include one): wrap at 76 chars, separated from subject by a blank line. Explain why, the diff shows what. State facts: banish "likely", "probably", "might", "seems", "appears to". If you don't know what a change does, read more before committing. Two sentences usually suffices; mention load-bearing context a future bisect would want.

HEREDOC + Co-Author

Always pass messages via HEREDOC to preserve formatting. Add a Co-Authored-By trailer that names the model, "Claude" alone doesn't disambiguate across multi-agent sessions.

git commit -m "$(cat <<'EOF'
fix(auth): guard against null session in token refresh

Refresh racing with logout was dereferencing a freed session, surfacing
as a 500 with no log trail. Early return plus a single warn log makes
the failure mode visible without spamming on every refresh.

Co-Authored-By: Nova (Claude Opus 4.7) <noreply@anthropic.com>
EOF
)"

Examples

Multi-agent staging

Other agents may be working in parallel:

git status                # See the full picture first
git diff --staged         # Review what you're about to commit
git add <specific-files>  # Only files you personally touched

Never git add -A or git add . (catches other agents' WIP and secrets). Never git restore files you didn't modify. Never git push without explicit request, push is the human's call. Skip planning docs, scratch files, and .local.md from the repo.

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Anti-Patterns

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Cross-Model Review

For high-stakes changes, run /hyperskills:cross-model-review after implementation. A different reviewer model has different blind spots than the author and catches real bugs: migration idempotency, PII in debug logging, empty-array edge cases, missing batch limits. Use /hyperskills:codex-review only when you specifically want the Claude → Codex direction with codex review subcommand semantics.

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References

For quantitative benchmarks and implementation archetype templates, consult references/benchmarks.md.

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What This Skill is NOT

• Not a gate. Don't follow all five phases for a typo fix. Scale selection exists for a reason.
• Not a replacement for reading code. This skill tells you HOW to implement, not WHAT to implement.
• Not a planning tool. Use /hyperskills:plan for task decomposition.
• Not an excuse to skip tests. "Verify" means running actual checks, not eyeballing the diff.