dietrichgebert/ponytail

ponytail-review

Code review focused exclusively on over-engineering.

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Review diffs for unnecessary complexity. One line per finding: location, what to cut, what replaces it. The diff's best outcome is getting shorter.

Format

L<line>: <tag> <what>. <replacement>., or <file>:L<line>: ... for multi-file diffs.

Tags:

  • delete: dead code, unused flexibility, speculative feature. Replacement: nothing.
  • stdlib: hand-rolled thing the standard library ships. Name the function.
  • native: dependency or code doing what the platform already does. Name the feature.
  • yagni: abstraction with one implementation, config nobody sets, layer with one caller.
  • shrink: same logic, fewer lines. Show the shorter form.

Examples

❌ "This EmailValidator class might be more complex than necessary, have you considered whether all these validation rules are needed at this stage?"

L12-38: stdlib: 27-line validator class. "@" in email, 1 line, real validation is the confirmation mail.

L4: native: moment.js imported for one format call. Intl.DateTimeFormat, 0 deps.

repo.py:L88: yagni: AbstractRepository with one implementation. Inline it until a second one exists.

L52-71: delete: retry wrapper around an idempotent local call. Nothing replaces it.

L30-44: shrink: manual loop builds dict. dict(zip(keys, values)), 1 line.

Scoring

End with the only metric that matters: net: -<N> lines possible.

If there is nothing to cut, say Lean already. Ship. and stop.

Boundaries

Scope: over-engineering and complexity only. Correctness bugs, security holes, and performance are explicitly out of scope. Route them to a normal review pass, not this one. A single smoke test or assert-based self-check is the ponytail minimum, not bloat, never flag it for deletion. Does not apply the fixes, only lists them. "stop ponytail-review" or "normal mode": revert to verbose review style.

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dietrichgebert
社区

ponytail

Forces the laziest solution that actually works, simplest, shortest, most minimal. Channels a senior dev who has seen everything: question whether the task needs to exist at all (YAGNI), reach for the standard library before custom code, native platform features before dependencies, one line before fifty. Supports intensity levels: lite, full (default), ultra. Use on ANY coding task: writing, adding, refactoring, fixing, reviewing, or designing code, and choosing libraries or dependencies. Also use whenever the user says "ponytail", "be lazy", "lazy mode", "simplest solution", "minimal solution", "yagni", "do less", or "shortest path", or complains about over-engineering, bloat, boilerplate, or unnecessary dependencies. Do NOT use for non-coding requests (general knowledge, prose, translation, summaries, recipes).

安装量
4.8万
GitHub Stars
11.8万
最近更新
8月7日
dietrichgebert
社区

ponytail-audit

Whole-repo audit for over-engineering. Like ponytail-review, but scans the entire codebase instead of a diff: a ranked list of what to delete, simplify, or replace with stdlib/native equivalents. Use when the user says "audit this codebase", "audit for over-engineering", "what can I delete from this repo", "find bloat", "ponytail-audit", or "/ponytail-audit". One-shot report, does not apply fixes.

安装量
268
GitHub Stars
11.8万
最近更新
8月7日
dietrichgebert
社区

ponytail-debt

Harvest every ponytail: comment in the codebase into a debt ledger, so the deliberate shortcuts and deferrals ponytail leaves behind get tracked instead of rotting into "later means never". Use when the user says "ponytail debt", "/ponytail-debt", "what did ponytail defer", "list the shortcuts", "ponytail ledger", or "what did we mark to do later". One-shot report, changes nothing.

安装量
249
GitHub Stars
11.8万
最近更新
8月7日
dietrichgebert
社区

ponytail-gain

Show ponytail's measured impact as a compact scoreboard: less code, less cost, more speed, from the benchmark medians. One-shot display, not a persistent mode, and not a per-repo number. Trigger: /ponytail-gain, "ponytail gain", "what does ponytail save", "show ponytail impact", "ponytail scoreboard".

安装量
242
GitHub Stars
11.8万
最近更新
8月7日