Agentic Coding Platform Skills
Delegieren Sie ganze Aufgaben an einen IDE-Agenten — und verifizieren Sie alles, was er ausliefert.
Verwandelt Ihre KI in einen Teamkollegen auf einer Coding-Plattform — wählt den richtigen Agenten-Modus für jede Aufgabe, nimmt delegierte Briefings entgegen, zerlegt Änderungen über mehrere Dateien in Checkpoints und beweist jede Änderung mit einer Verifikationsschleife, bevor sie ausgeliefert wird.

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Was ist enthalten
Eine SKILL.md (die Anleitung) + eine Startvorlage. Eine Vorschau:
Agentic Coding Platform Skills
When to use
- You work in an editor or IDE with built-in agent features and want to use them deliberately instead of clicking whichever mode is nearest
- A task spans many files — a refactor, a feature with backend plus frontend plus tests — and one-shot edits keep breaking something three files away
- You want to delegate whole tasks to the agent while keeping real control: you decide the brief, the checkpoints, and what counts as verified
- You have run two or more agents in parallel and watched them overwrite each other's work or solve the same problem twice
- Your agent's changes look finished but fail in ways a short verification pass would have caught
Workflow
- Choose the agent mode for the task (input: task → output: mode + reason)
Agent modes are not flavours — they are different permission levels. A question needs the lightest mode (read and answer, change nothing). A small fix needs edit mode on named files. A whole feature needs full agent mode with planning. Pick the lightest mode that can do the job and write down why: the mode decision is the first control, and it is made before the agent starts, not after it has already wandered. - Delegate with a task brief (input: task + mode → output: task brief)
Write the brief the way you would brief a capable colleague: goal, context, files in scope, files out of scope, constraints, and how success will be checked. Include what "done" excludes — "do not redesign the settings page, do not change the API shape." A brief without exclusions is an invitation to remodel the whole house while fixing a tap. - Split multi-file work into checkpoints (input: task brief → output: checkpoint plan)
Break the change into checkpoints that each leave the project working: first the data shape, then the logic, then the interface, then the tests. One checkpoint per coherent step, each with its own check. If a checkpoint cannot be described in one sentence, it is two checkpoints pretending to be one. The agent works checkpoint by checkpoint and stops at each — it never races ahead to "finish" while an early checkpoint is still red. - Run the verification loop (input: completed checkpoint → output: verification result)
Every checkpoint ends the same way: build, tests, and a manual look at the behaviour in the running app. The loop is build → test → observe → fix → repeat, and the checkpoint only passes when all three agree. A green test suite with a broken screen is not a pass; a working screen with a failing test is not a pass either. Verification is a loop, not a single command. - Reconcile parallel agents (input: two or more agent outputs → output: one merged change)
When agents run in parallel, give each one a separate slice with no shared files, and merge in a fixed order: shared foundations first, then the slices that depend on them. Before merging, diff each agent's work against the same base and read for overlap — two agents "improving" the same helper is the classic collision. One human does the merge; agents do not merge each other's work unsupervised. - Promote the change to the team (input: verified change → output: review-ready change)
Turn the verified work into something a teammate can review in minutes: a short summary of what changed and why, the checkpoint list with verification results, and the diff. If the summary is longer than the diff is complicated, rewrite the summary. The agent's job ends at verified; your job ends at reviewable.
Vorschau der Startvorlage
Agentic Coding Platform — Task Brief Template
One task = one brief, one checkpoint plan, one verification trail.
Mode decision
Task: {one sentence}
Mode chosen: {read-only / edit / full agent} — Reason: {why this is the lightest mode that can do the job}
Task brief
Goal: {what the finished work does}
Context: {why now, what it connects to}
In scope: {files / areas the agent may change}
Out of scope: {files / areas it must not touch}
Constraints: {API shape, style, performance, compatibility — list}
Success check: {how we will know it works, in observable terms}
Das Skill-Paket selbst (SKILL.md + Vorlage) ist auf Englisch verfasst.


