Ln 41 Surgical Change Implementer logo

Ln 41 Surgical Change Implementer

Community
levnikolaevich
ln-41-surgical-change-implementer

Implements one scoped feature or fix through the smallest complete solution; not upgrades or performance tuning.

Overview

Publisherlevnikolaevich
Repositoryclaude-code-skills
Skill nameln-41-surgical-change-implementer
Stars
565
Forks
84
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by levnikolaevich on GitHub. Read the source before you install it.

Installation

Install the Ln 41 Surgical Change Implementer AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/levnikolaevich/claude-code-skills.git /tmp/claude-code-skills
mkdir -p .claude/skills
cp -r /tmp/claude-code-skills/plugins/implementation-suite/skills/ln-41-surgical-change-implementer .claude/skills/ln-41-surgical-change-implementer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ln 41 Surgical Change Implementer in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Ln 41 Surgical Change Implementer on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Ln 41 Surgical Change Implementer is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Surgical Change Implementer

Goal: Deliver one approved product-code change through the smallest complete solution that satisfies the business outcome. Remove superseded code and avoid speculative abstraction, duplicate mechanisms, and custom infrastructure already provided by the repository or platform.

Execution contract: The checklist defines completion. Track each item internally as PENDING, PROVEN with evidence, CLEARED with evidence its condition is absent, or UNPROVEN with a gap; reading, delegation, or tool failure is not proof. Reconcile after each section. Before returning, resolve all PENDING, count only PROVEN and CLEARED, and apply verdict and approval rules to every gap. Preserve intent, scope, and existing authorization. Continue authorized work; ask only for consequential unresolved choices or required external approval. Scale depth to material risk without skipping checks. Preserve dependency and safety order; otherwise choose an appropriate verification method. Accept equivalent user or repository evidence; no other skill, named artifact, or complete lifecycle is required. Preserve source requirement and decision IDs. Bind reused evidence to relevant source versions, dirty changes, configuration, and environment; invalidate only affected claims. On continuation, reconcile task, authorization, current state, and unresolved evidence. For long work, return a compact continuation record or update an already authorized artifact; read-only skills do not persist it. Distinguish artifact readiness, verified behavior, and external-action authority. Prepare authorized work before required approval. If blocked by an instruction, cite its exact source and unresolved boundary; do not invent approval gates from caution.

Tool Routing

NeedPreferred capabilityFallback
Scope and repository policyUser request, linked task or plan, repository instructions, Git status, and focused diffState bounded assumptions; stop if a choice would materially change product intent
Runtime ownership and impactLanguage server, host-native code intelligence, traces, schemas, routes, and configurationNarrow symbol and text search followed by direct reads of definitions and consumers
Existing capabilityRepository code, manifests, lockfiles, platform APIs, and installed dependency sourceCurrent official documentation and primary sources; mark uncertain claims UNVERIFIED
Safe implementationFocused editor, native formatter, package manager, and generation commandsMinimal manual patch that preserves user changes and generated-file ownership
VerificationRepository-defined build, lint, type, test, smoke, and runtime checksSmallest reproducible check that proves the protected contract; disclose coverage gaps
External semanticsOfficial documentation, specifications, security advisories, registries, and upstream sourcePrimary-source technical material; use secondary expert guidance only for tradeoffs

Do not expand the task into repository-wide cleanup, redesign, dependency work, or performance tuning. Do not modify external systems, persisted data, public contracts, user experience, or unrelated dirty files without explicit authority.

Core Rules

  • Surgical does not mean superficial. Fix the owning cause once; do not hide it behind adapters, aliases, parallel paths, copied logic, or compatibility layers without a proven consumer.
  • Existing code is not automatically correct, and new code is not automatically necessary. Subtraction, configuration, or no code can be the best implementation.
  • Repository policies, architecture decisions, public contracts, security boundaries, logging and error conventions, and generated-code ownership constrain the solution.
  • Research a concrete semantic or design uncertainty before coding. Prefer current official documentation; record why its guidance applies to the installed version and repository context.
  • Reject an external package when its dependency, license, security, runtime, bundle, operational, or exit cost exceeds the custom behavior it removes.
  • Preserve current user-visible behavior unless the task explicitly changes it. Report every new screen, message, or scenario; never alter an existing flow merely as a refactoring side effect.
  • Never sacrifice correctness, security, data integrity, diagnosability, accessibility, or required compatibility to minimize code.

Checklist

1. Establish the Change Contract

  • Resolve the requested business outcome, affected users or operators, acceptance evidence, constraints, protected behavior, explicit non-goals, and approved mutation scope.
  • Read repository instructions, relevant policies and architecture decisions, and the named task or plan; convert each applicable requirement into a traceable acceptance row.
  • Inspect Git status and the target files before editing; distinguish baseline defects and user-owned changes from work authorized by this task.
  • Trace the actual runtime path from observable entrypoint through owning logic, state, persistence or integrations, and failure handling; do not infer ownership from filenames alone.
  • Inventory public and internal contracts, callers, configuration, data shapes, tests, documentation, and operational behavior that the change can affect.
  • Identify decisions affecting product intent, UX, compatibility, data, dependencies, or external state. Use existing task authorization; ask only when a consequential choice is unresolved or would expand scope.
  • Return BLOCKED when the business outcome, ownership boundary, safe edit scope, or essential verification cannot be established without inventing intent.

2. Choose the Smallest Complete Solution

  • Test NO_CHANGE: verify whether the outcome already holds without edits; a usage explanation may suffice. Documentation or configuration edits belong to DELETE_OR_CONFIGURE and require verification as changes.
  • Test DELETE_OR_CONFIGURE: identify an obsolete path, wrong default, redundant state, feature flag, registration, or configuration that can be removed or corrected directly.
  • Test REUSE_LOCAL: search for the repository's canonical helper, component, service, policy, type, enum, constant, error, or integration before adding another concept.
  • Test USE_PLATFORM_OR_STDLIB: verify whether the language, runtime, browser, database, framework, or deployment platform already owns the required generic behavior.
  • Test REUSE_INSTALLED: inspect declared dependencies and their supported APIs before proposing a new package or custom mechanism.
  • Consider ADOPT_DEPENDENCY only when remaining behavior is generic and material; verify current official guidance, maintenance, security, license, compatibility, transitive cost, and removal path.
  • Use MINIMAL_CUSTOM for irreducible product policy or a documented capability or lifecycle-cost gap; name the invariant and why applicable simpler options are insufficient.
  • Stop searching when a candidate completely satisfies the contract at acceptable lifecycle cost; clear later rungs as unnecessary. Compare credible candidates by total complexity and risk, recording the chosen rung and rejected applicable simpler options.
  • Challenge the proposed design for symptom patches, duplicated ownership, speculative extension points, premature abstraction, hidden state, avoidable branching, and temporary compatibility that lacks a real consumer.
  • Define the coherent edit set, deletion set, verification, and rollback boundary before changing code.

3. Implement Surgically

  • Change the canonical owning boundary once and update only the consumers required for a complete end-to-end result.
  • Follow repository conventions for naming, types, constants, enums, configuration, errors, logging, security, accessibility, concurrency, transactions, and resource lifecycle.
  • Keep product policy explicit and centralized; do not scatter magic values, duplicated route or event keys, parallel allowlists, or derived state with multiple owners.
  • Use existing dependency and generation workflows; do not hand-edit lockfiles or generated artifacts, add convenience wrappers around already clear APIs, or copy third-party implementation code.
  • Before removal, verify allegedly unused paths against dynamic imports, reflection, registries, configuration, generation, scripts, optional features, and external consumers; static search alone cannot authorize deletion.
  • Remove obsolete branches, helpers, adapters, aliases, flags, exports, configuration, dependencies, documentation, and tests made unnecessary by the retained design.
  • Preserve compatibility only for a verified consumer; make every temporary bridge narrow, observable, owned, time-bounded by a removal trigger, and explicit in the report.
  • For deliberate simplifications with material, non-obvious limits, record current contract fit, supported bounds, an observable revisit trigger, and what to reconsider in a local comment or existing decision record within scope. Do not invent thresholds, mandate markers or registries, or document routine simplicity.
  • Inspect the diff during implementation for unrelated formatting, opportunistic refactoring, accidental UX or contract changes, debug artifacts, and net-new code unsupported by the change contract.

4. Build Proportionate Evidence

  • Map each acceptance row and material regression risk to existing evidence before adding tests; assess likelihood, impact, detectability, and blast radius.

  • Choose exactly one portfolio action per affected test or gap: KEEP, ADD, UPDATE, MERGE, DELETE, or justified NO_TEST; remove superseded and low-value testware in the approved scope.

  • Test value and boundary: Require every test to detect a concrete defect in this product's business logic and name the protected business outcome. Prefer E2E through user or external-system boundaries; use integration or unit tests only for business scenarios difficult to exercise reliably through E2E. Reject platform, trivial-wiring, implementation-detail, and duplicate proof with no distinct business failure signal.

  • UI test locators: Use stable project-native semantic locators (roles, accessible names, labels) or explicit IDs/test hooks according to the observable contract and locale strategy. Avoid styling, position, timing, and incidental structure. Treat exact-copy assertions separately when copy is a requirement; do not require product edits solely to add hooks when a robust semantic locator exists.

  • Give temporary characterization or migration tests an owner and retirement trigger; keep quarantine explicit and never count skipped, flaky, or unproven evidence as passing.

  • Run focused checks after the coherent edit, then the repository-required build, lint, type, test, smoke, packaging, and application-start gates relevant to the affected path.

  • Exercise meaningful failure, boundary, authorization, transaction, concurrency, or rollback behavior when the change contract makes it material.

5. Prove Completeness and Finalize

  • Trace every applicable task or plan requirement to the final code path and observed result; do not infer completion from a clean build or the presence of changed files.
  • Search for stale names, old mechanisms, duplicate routes or registrations, dead exports, compatibility aliases, obsolete configuration and documentation, and unnecessary tests within the affected capability.
  • Review the complete diff against the approved scope and explain every changed file; remove changes that do not contribute to the business outcome or required evidence.
  • Verify the retained solution remains the simplest complete rung after implementation; collapse wrappers, intermediate states, and abstractions that no longer protect a demonstrated invariant.
  • If verification fails, distinguish baseline/environment failures from change-caused defects; repair the latter within scope and rerun affected checks. Keep working until acceptance passes or a concrete prerequisite prevents progress. Mark KEEP only with passing required evidence; use DISCARD and revert only run-owned edits when the approach is unsuitable or cannot be completed safely, preserving user work.
  • Preserve unrelated user work, clean only run-owned temporary artifacts, and confirm no unapproved external or persisted state changed.
  • Verify the delivered increment works with its required consumers and prior increments; reconcile changed requirements against dependent implementation and acceptance evidence before claiming completeness.
  • Use DELIVERED for a kept, fully implemented and verified outcome; NO_CHANGE only when the requested outcome already holds without edits; BLOCKED when a required decision, proof, safe completion, or restoration path is unavailable. A discarded attempt is not a satisfied request: report the unresolved outcome and restoration state.

Self-Check

  • Reconcile before returning. Check item-level evidence, requirement coverage, contradictions, scope, verdict, and applicable cleanup. Correct the report or authorized artifacts. Reuse valid evidence; do not automatically rescan the repository or rerun successful commands. Repeat checks only for relevant changes, failures, or unresolved evidence. Disclose remaining gaps.

Output Contract

Report in the user's language, in this order; retain all five fields and state each fact once. Small results may use one line per field; omit empty tables and do not copy linked artifacts:

  1. Result: Skill-specific verdict and supported outcome.
  2. Scope: Reviewed/changed scope, exclusions, baseline, and material assumptions.
  3. Evidence: Skill-specific fields below; distinguish facts, inferences, and unverified claims. Link artifacts; use tables when useful.
  4. Verification: Checks/results, unavailable evidence, and applicable cleanup/external state.
  5. Completion: Checklist: X/Y complete; Incomplete: None or each UNPROVEN item's reason, outcome impact, and exact next action; residual risks and required decisions.

Skill-specific evidence: Business outcome, protected behavior, mutation scope, non-goals, and affected runtime path. Record selected solution rung and evidence for rejecting applicable simpler options. Map acceptance requirement → owning change → observed evidence → result. Include additions/removals, justified compatibility, test portfolio actions and independent oracles, required gates, deviations, cleanup, and unresolved risks; distinguish an already-satisfied request from an unsuccessful reverted attempt.

Frequently asked questions

What does the Ln 41 Surgical Change Implementer AI skill do?

Implements one scoped feature or fix through the smallest complete solution; not upgrades or performance tuning.

Why use Ln 41 Surgical Change Implementer on TypingMind?

Because you install it once and use it with any model. Ln 41 Surgical Change Implementer is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Ln 41 Surgical Change Implementer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/levnikolaevich/claude-code-skills/tree/master/plugins/implementation-suite/skills/ln-41-surgical-change-implementer. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Ln 41 Surgical Change Implementer?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Ln 41 Surgical Change Implementer?

As many as you like. As long as a model supports skills, you can use Ln 41 Surgical Change Implementer with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Ln 41 Surgical Change Implementer AI skill free?

Yes. It is published on GitHub by levnikolaevich under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇