adhd

Tinjau · 65
Diindeks di Registry

Parallel divergent ideation — spawns N isolated generator agents under different cognitive frames (regulator, biology, speedrunner, 10-year-old, zero-budget), then a critic pass scores, clusters, prunes traps, and deepens the top 3. Use for open-ended design, architecture, naming

Verified installs0
Star42
Versi1.0.0
Kualitas63/100 · Menjanjikan
Kepercayaan65/100 · Hanya sandbox
Audit77/100 · Perlu ditinjau

Profil aset

Agent pemrograman dan pengembangan

Code review, repo analysis, testing, CI, GitHub, DevOps, and developer workflow skills.

Lihat kategori

Skenario

Agent pemrograman

I need a coding agent that can understand a repository, edit code, and review pull requests.

Kecocokan Agent

Claude Code + CLI + Codex

Cocok untuk Codex, Claude Code, Cursor, CLI, atau Agent khusus.

Pasang

Siap

npx skills add darkroomengineering/cc-settings --skill adhd

Pemeliharaan

Terkini

2 hari sejak push

Risiko

Perlu ditinjau

Dependency or permission surface needs review

Kualitas GitHub

42

63/100 Kualitas · 73/100 Kepercayaan

Tag cakupan

CodingAgent pemrogramanDesain dan kreatifagent-skill

Catatan ulasan

Dependency or permission surface needs review · Permission surface may require sandboxing

Kartu adopsi Agent

Kepercayaan, audit, dan kesiapan pemasangan dalam sekali lihat

Skor ini menggabungkan metadata repositori publik, sinyal ulasan OpenAgentSkill, kebaruan pemeliharaan, dan kesiapan pemasangan. Ini adalah sinyal shortlist, bukan pengganti peninjauan manusia.

Kualitas

Menjanjikan
63

Useful candidate, but compare it with alternatives before adopting.

Kepercayaan

Hanya sandbox
65

Kandidat berguna dengan sinyal kepercayaan yang kurang atau bercampur. Gunakan di ruang kerja terisolasi hingga loop hasil membuktikan kecocokan tugas.

Audit

Perlu ditinjau
77

Tinjauan yang dapat dibaca mesin tentang kesiapan pemasangan, metadata keamanan, pemeliharaan, dan risiko adopsi.

Trust Score OpenAgentSkill v5

Tinjauan manusia sebelum pemasangan

Jalankan hanya dalam sandbox dan bandingkan alternatif terdekat sebelum digunakan untuk kerja nyata.

CodexClaude CodeCursorOpenAgentSkill CLI

Star

42 star GitHub

Aktivitas repositori

42 star dan 3 fork

Pemeliharaan

2 hari sejak push

Lisensi

MIT

Pasang

npx skills add darkroomengineering/cc-settings --skill adhd

Keamanan pemasangan

Jalur pemasangan paket atau runtime standar

Cakupan izin

shell or command execution, network or browser access

Hasil Agent

Belum ada data hasil Agent

Dokumentasi

Konteks README/SKILL.md kuat

Ringkasan risiko

Tinjau sebelum produksi

  • Financial research output is not financial advice; require human review before any live investment decision.
  • Low GitHub adoption signal
  • Quality score needs review
  • Permission surface needs review: shell or command execution, network or browser access

Kesiapan pemasangan

Jalur pemasangan tersedia

  • Jalur pemasangan tersedia
  • Bukti repositori tersedia
  • Lisensi dinyatakan
  • Belum ada bukti hasil Agent-Proven

Metadata yang dapat dibaca Agent

Data keputusan yang dapat dibaca mesin untuk skill ini.

Gunakan blok ini atau JSON tersemat untuk memutuskan apakah Agent perlu memasang skill ini, memilih alternatif, atau meminta tinjauan manusia terlebih dahulu.

Buka JSON

Tugas yang sesuai

  • alur kerja Agent pemrograman
  • Tim Claude Code
  • builders willing to evaluate younger projects
  • Inspect source files

Agent yang sesuai

CodexClaude CodeCursorOpenAgentSkill CLICLI

Keputusan pemasangan

Perintah
npx skills add darkroomengineering/cc-settings --skill adhd
Kebijakan
Tinjau
Tinjauan manusia
Ya

Kepercayaan dan risiko

Kepercayaan
65/100
Audit
77/100
Tingkat risiko
Perlu ditinjau

Lingkar hasil

Endpoint
/api/agent/outcome
ID event
resolve
Hasil
5

Perintah pemasangan

npx skills add darkroomengineering/cc-settings --skill adhd

Jangan gunakan ketika

  • Tim yang membutuhkan SLA dengan dukungan vendor
  • production agents without a repository review
  • Low GitHub adoption signal
  • Petunjuk izin berisiko tinggi: eksekusi shell atau perintah
  • Dependency or permission surface needs review

Keamanan Agent v2

45/100 · Hindari pemasangan otomatis

EksperimentalTinjau

Sparse or mixed signals. Useful for discovery, but not for autonomous installation.

Test manually in an isolated workspace and compare against safer alternatives.

Selesaikan via API

Tinggi

Eksekusi shell atau perintah

Metadata skill merujuk terminal, CLI, shell, subprocess, atau alur kerja eksekusi perintah.

Sedang

Browser automation

Skill may drive a browser or interact with web pages.

Sedang

Akses jaringan

Skill kemungkinan mengambil halaman jarak jauh, API, repositori, atau layanan eksternal.

Sedang

Akses database

Skill dapat memeriksa skema, mengkueri database, atau bekerja dengan penyimpanan persisten.

  • Petunjuk izin berisiko tinggi: eksekusi shell atau perintah
  • Dependency or permission surface needs review

Target pemasangan

Pasang skill ini di alur Agent Anda

Gunakan endpoint publik untuk mengambil perintah, checklist keamanan, prompt target, dan tautan kanonis.

skill install

OpenAgentSkill CLI

Resolve policy, run the source installer safely, and report a verified install receipt.

$ npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install darkroomengineering-adhd

Rencana resolusi Agent

Biarkan Agent memverifikasi kecocokan sebelum memasang.

API Resolve mengembalikan skill utama, alternatif, kebijakan keamanan, catatan audit, target pemasangan, dan prompt siap pakai.

Buka rencana teks

Agent harus memeriksa

  • Task fit and alternatives from Resolve API.
  • Audit score, trust score, and safety policy warnings.
  • Install target compatibility for Codex, Claude Code, Cursor, or CLI.

Salin prompt

Task: Use adhd in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20adhd%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/darkroomengineering-adhd/install
Install command: npx skills add darkroomengineering/cc-settings --skill adhd
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.

Serah-terima Agent

Berikan jalur pemasangan kepada Agent, bukan direktori lain.

Gunakan endpoint publik untuk mengambil perintah, checklist keamanan, prompt target, dan tautan kanonis.

Buka API pemasangan

Prompt Agent

Use adhd for this task. Review https://www.openagentskill.com/api/skills/darkroomengineering-adhd/install, then install with: npx skills add darkroomengineering/cc-settings --skill adhd

Metadata Registry

Profil yang dapat dibaca Agent untuk pemilihan skill otomatis.

API Registry menyediakan sinyal keputusan, kepercayaan, audit, use case, dan pemasangan tanpa mengikis UI.

Buka Manifest

Kecocokan Agent

63/100

Agent pemrograman

Platform

Claude Code

Laporan audit

Perlu ditinjau · 77/100

Tinjauan yang dapat dibaca mesin tentang kesiapan pemasangan, metadata keamanan, pemeliharaan, dan risiko adopsi.

Lihat laporan auditLihat laporan evaluasi

Panel keputusan Agent

Fallback candidate for Coding agents

Prototype with this skill first; keep a fallback candidate ready.

63
Kesiapan
Prototipe
Tahap

Peran di stack

Kandidat cadangan

Kecocokan utama

Agent pemrograman

Label kepercayaan

Buat prototipe dulu

Jalur pemasangan

Perintah siap

Gunakan saat

  • alur kerja Agent pemrograman
  • Tim Claude Code
  • builders willing to evaluate younger projects

Bukti

  • recent repository activity
  • install command or GitHub repo available
  • profil kualitas 63/100
  • 3 event interaksi OpenAgentSkill

tinjau dulu

  • Low GitHub adoption signal

Jalur implementasi

  1. 1Pasang di Agent sandbox dan jalankan satu tugas Agent pemrograman dari awal hingga akhir.
  2. 2Compare output quality, latency, and failure behavior against at least one alternative.
  3. 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.

Profil kepercayaan

Hanya sandbox

Kandidat berguna dengan sinyal kepercayaan yang kurang atau bercampur. Gunakan di ruang kerja terisolasi hingga loop hasil membuktikan kecocokan tugas.

65
Trust Score OpenAgentSkill

Adopsi GitHub

Periksa

42 star GitHub

Aktivitas star/fork

Periksa

42 star dan 3 fork; aktivitas issue tidak tersedia dalam metadata saat ini

Pemeliharaan terbaru

Lulus

2 hari sejak push

Kejelasan lisensi

Lulus

MIT

Sinyal positif

  • Tinjauan AI disetujui
  • Jalur pemasangan tersedia
  • Bukti repositori tersedia
  • Repositori yang baru dipelihara
  • Perintah pemasangan tidak memiliki pola berisiko tinggi yang jelas
  • Loop hasil siap tetapi membutuhkan eksekusi Agent nyata pertama

Tinjau sebelum memasang

  • Financial research output is not financial advice; require human review before any live investment decision.
  • Low GitHub adoption signal
  • Quality score needs review
  • Permission surface needs review: shell or command execution, network or browser access
  • GitHub adoption: 42 GitHub stars
  • Stars/forks activity: 42 stars, 3 forks; issue activity unavailable in current metadata
  • Dependency/runtime risk: command execution surface, network or browser surface
  • Permission surface: shell or command execution, network or browser access
  • Belum ada laporan hasil Agent nyata
  • Tinjauan manusia diperlukan sebelum pemasangan tanpa pengawasan

Tindakan yang disarankan

Jalankan hanya dalam sandbox dan bandingkan alternatif terdekat sebelum digunakan untuk kerja nyata.

Profil kualitas

Menjanjikan kandidat untuk alur kerja Agent

Useful candidate, but compare it with alternatives before adopting.

63
Star GitHub
42
Keterkinian
2 hari lalu
Siap dipasang
Ya
Lisensi
MIT
Tinjau sebelum memasang: Low GitHub adoption signal

Kecocokan alur kerja

Gunakan skill ini pada skenario berikut

Kecocokan alur kerja

Tambahkan ke alur kerja lengkap

Daftar alternatif

Bandingkan sebelum memasang

Similar skills that may fit this task.

Bandingkan semua

Ringkasan

--- name: adhd argument-hint: "[problem]" description: Parallel divergent ideation — spawns N isolated generator agents under different cognitive frames (regulator, biology, speedrunner, 10-year-old, zero-budget), then a critic pass scores, clusters, prunes traps, and deepens the top 3. Use for open-ended design, architecture, naming, API/SDK surface, and fuzzy debugging where the obvious answer is expensive to get wrong. Triggers "/adhd", "adhd mode", "brainstorm", "ideate", "widen the option space", "divergent ideas", "we keep landing on the same idea". Skip for lookups, syntax, bugs with a known root cause, or closed phrasing ("quick", "standard", "canonical", "textbook"). Use /oracle compare to evaluate options you already have — adhd generates the option space; use /plan-ceo-review to challenge whether to build at all. context: main license: MIT ---

# ADHD

Stop picking the textbook answer. The first three answers the model would give are the answers a senior engineer would give in thirty seconds. Correct. Forgettable. The interesting answers live past number three, in the awkward middle nobody walks into. This skill makes the model walk there.

## When to use vs siblings

- `/adhd` — **generate** the option space when you don't have candidates yet. - `/oracle` (compare mode) — **evaluate** options you already have. - `/plan-ceo-review` — challenge whether the thing should be built at all. - `/verify` — adversarially check a conclusion you've already reached.

They compose: `/adhd` to widen, `/oracle` to weigh the shortlist.

## Pre-flight (run before Phase 1)

This skill is expensive. About 10 Agent calls, 30 to 90 seconds wall clock, 5 to 10x a single answer. Do not pay that cost when a direct answer is better. Run this gate before Phase 1.

**Step 1. Explicit invocation check.**

If the user typed `/adhd` or explicitly asked for ADHD mode, "use the adhd skill", or "run ADHD on this", **SKIP the rest of this section and go straight to Phase 1**. The user opted in. Do not second-guess.

**Step 2. Self-judge (only if Step 1 did not match).**

Ask yourself three questions. If the answer to any is no, ABORT.

1. **Open-ended?** Would a senior engineer give multiple viable answers here, or is there one canonical answer? If canonical, abort. 2. **High-stakes?** Is the cost of the obvious answer being wrong actually high? Architecture decisions, public API surfaces, naming a real product, fuzzy bugs with no known root cause, schema design = yes. Side project at 11pm = no. 3. **Open phrasing?** Did the user avoid words like "quick", "standard", "canonical", "textbook", "just", "one-line"? If they used any of those, they want the direct answer. Abort.

If all three checks pass, proceed to Phase 1.

If any fails, ABORT and answer the question directly. Optionally append one sentence: *"If you want a wider exploration under parallel cognitive frames with explicit trap detection, run `/adhd <your problem>`."*

## The loop

Two strict phases. Mixing them kills idea quality, because the critic strangles the generator.

### Phase 1 — Diverge (no critic)

For the problem P:

1. Pick 5 cognitive frames from the table below. Bias toward engineering tags when the problem is code-shaped. Always include at least one wild frame to keep range.

2. Spawn 5 **parallel** Agent tool calls in ONE message. One per frame. Each Agent gets only: - the problem P - any context the user provided - the chosen frame's vantage prompt - a system instruction that forbids evaluation

The exact instruction to give each Agent:

> You are in DIVERGENT mode. You are a generator, not a critic. > Generate 6 short distinct ideas under this frame. Each idea is one > phrase or one sentence. Do not evaluate. Do not rank. Do not hedge. > The first three obvious answers everyone would give are banned. > Push past them into the awkward middle. > Output a JSON array only. No prose before or after. > `[{"text": "...", "rationale": "..."}, ...]`

3. **Critical invariant.** The Agent calls must be parallel and isolated. Do NOT serialize them. Do NOT pass one branch's output as context to another. Branches that see each other anchor each other and the whole method collapses to a wider single thought.

### Phase 2 — Focus (critic on)

After all branches return:

1. **Score.** Rate each idea on three axes 0 to 10: novelty (distance from the obvious default), viability (could it actually ship), fit (does it address the stated problem). For any idea that looks attractive but is a trap (hidden cost, false economy, will not scale, premature abstraction), flag it with a one-line reason.

2. **Cluster.** Group ideas into 3 to 6 clusters by their underlying angle, not by surface keywords. Label clusters by angle: "remove the server plays", "cache-shaped plays", "batched-window plays", "race-multiple- backends plays".

3. **Deepen the top 3.** Rank by weighted score (novelty 0.35 + viability 0.40 + fit 0.25), exclude traps, take top 3. For each, spawn one Agent call that produces: - a 4 to 8 sentence sketch of how the idea works - the load-bearing risk - the first concrete step a builder would take - 3 to 5 child ideas (variations, hybrids, unlocks)

Deepen Agent instruction:

> You are in FOCUS mode. Take one promising idea and connect dots. > Sketch how it would actually work in 4 to 8 sentences. Name the > load-bearing risk. Name the first concrete step a coder would take. > Then generate 3 to 5 sub-ideas that branch off (variations, > combinations with other domains, things this unlocks). > Output JSON only.

Scoring, clustering, and the final synthesis stay in the main session — that is judgment work and belongs on the session's top-tier model. The generator and deepen agents are fan-out subagents and inherit `CLAUDE_CODE_SUBAGENT_MODEL` (Sonnet), which fits the quota doctrine: roomy pools carry volume, the scarce pool does the judging.

## Frames

Pick 5 per run.

| Frame | Vantage prompt | Tags | |---|---|---| | **hardware engineer** | You think in latency, memory layout, and physical constraints. Re-ask this as a hardware/firmware problem. What does the bus topology, cache, timing budget tell you? | code, wild | | **regulator** | You audit systems for compliance and failure modes. What must be provable, traceable, or refusable here? | design, general | | **10-year-old** | You are a curious 10 year old who has never seen software. Describe naive but unencumbered approaches. Ignore convention. | general, wild | | **competitor trying to break it** | You are a hostile competitor or attacker. Generate approaches that exploit, fail, or sabotage the obvious solution. Then invert into ideas. | code, design | | **biology** | Transplant a mechanism from biology (immune systems, neural plasticity, cell signaling, evolution, gut flora). Force-fit it onto this engineering problem. | code, wild | | **logistics** | Steal mechanisms from logistics: queues, batching, just-in-time, hub-and-spoke, returns, last-mile. Apply them literally. | code, design | | **game design** | Approach this as a game designer. What are the loops, rewards, friction, save-states, speedrun tricks? Treat the user as a player. | design, general | | **markets** | Treat the problem as a market. Buyers, sellers, market-makers. What does an auction, a futures contract, a clearing house look like here? | design, wild | | **inversion** | Ask the OPPOSITE question. If goal is X, brainstorm how to guarantee NOT X. Then negate each answer back. | code, design, general | | **extreme: $0 budget, 1 hour** | No money, no team, one hour. What is the crudest version that still does the load-bearing thing? | code, general | | **extreme: infinite budget, 10 years** | Infinite compute, infinite engineers, a decade. What is the maximalist version? | design, wild | | **remove the load-bearing assumption** | Name the thing everyone treats as fixed (framework, database, request-response model, network). Imagine it is gone. What is possible? | code, design, wild | | **speedrunner** | You are a speedrunner. Find glitches, skips, out-of-bounds tricks, frame-perfect shortcuts. What is the abusive-but-legal path? | code, wild | | **ant colony** | No central planner. Many dumb agents, local rules, pheromone trails. How does the problem solve itself emergently? | code, wild | | **3am on-call** | You are the on-call engineer woken at 3am when this breaks. What design would let you not get paged? | code, design |

### Picking frames

For code-shaped problems: pick 4 frames tagged `code` or `design`, plus 1 tagged `wild`. For open product or strategy problems: a mix from all tags. Vary the picks across sessions so the same problem produces different candidate sets when re-run.

## Output shape

After Phase 2, render in this order. Do not collapse it into a wall of prose. The structure is the point.

1. **Brief.** One or two lines confirming the problem and any reframe used. 2. **Wide set.** Full pool grouped by cluster. Each cluster labeled by underlying angle. Each idea is one short phrase. Show score chips like `[N7 V8 F9]` next to each. 3. **Converge.** A 2 to 4 idea shortlist. State why each is on the list. Mark the non-obvious-but-viable pick explicitly with ★. List traps separately, each with the one-line reason it is a trap. 4. **Focus.** The 3 deepened branches. For each: the sketch, the load- bearing risk, the first concrete step, and the child ideas. 5. **Provocation.** One wildcard question or idea that opens a new direction the user can push into if nothing landed.

## Anti-patterns

These are how this skill goes wrong. Watch for them.

- **Convergence disguised as divergence.** Ten minor variations of one idea is not breadth. If every candidate shares the same underlying assumption, you have not diverged. You have decorated. - **Weird-for-weird's-sake with no convergence.** A pile of 30 unsorted absurdities is as useless as one safe answer. Always converge. - **Walls of equally-weighted prose.** Cluster, label, pull out the best. Structure is half the value. - **Refusing to commit.** After diverging, take a position on what is actually promising. "Here are 20 ideas, you decide" is a cop-out. Generate wide, but converge with a real opinion. - **Skipping the isolation invariant.** If you simulate parallel branches by writing them sequentially in one context, you have not done ADHD. You have done a wider single thought. The Agent tool gives each branch a fresh context. Use it.

## Calibration

- **How many ideas?** Scale to stakes. Quick "name this function" = 3 frames × 4 ideas. "How should I position this product" = 5 frames × 8 ideas. Default is 5 × 6 = 30. - **How weird?** Read the room. Serious strategy work: flag the wild cards clearly so they do not read as unserious. Open brainstorming or play: let it run loose. Absurd ideas earn their place by seeding viable ones. - **When to stop diverging?** Stop when new candidates start repeating the shape of existing ones. The space is mapped. Do not pad to hit a number.

## Cost

5 diverge + 1 score + 1 cluster + 3 deepen ≈ 10 Agent calls per run. About 5 to 10x a single-shot answer. Not for every keystroke. For decision points where the cost of the obvious answer is high. Diverge/deepen agents run on the Sonnet subagent pool, so the Opus/Fable cost of a run is one synthesis pass.

## Attribution

Ported from [`UditAkhourii/adhd`](https://github.com/UditAkhourii/adhd) (MIT). Upstream ships the same loop as an npm CLI (`adhd-agent`) plus evals and a source spec on divergent ideation; this port keeps the skill-only form (no install) and adds the cc-settings sibling-skill routing and subagent model notes.

Detail teknis

Versi
1.0.0
Lisensi
MIT
Pembaruan terakhir
20 Agu 2026
Diterbitkan
20 Agu 2026

Ringkasan keputusan

Kandidat cadangan

63
Siap
Prototipe
Tahap

recent repository activity

Audit

Tinjauan pemasangan

Tinjauan pemasangan dan adopsi

77
Perlu ditinjau
Keamanan
78/100
Pemeliharaan
100/100
Pasang
92/100
Buka audit lengkapLihat laporan evaluasi

Bukti tervalidasi Agent

Bukti tervalidasi Agent

Laporan hasil setelah resolve, tinjau, pasang, dan satu eksekusi terbatas.

0
Terbukti
Needs first agent runPasang otomatis: tinjau duluTerakhir: Tidak diketahui
Tingkat sukses
Kegagalan terbaru
Hasil
0
Kualitas output
Gagal
0
Tidak relevan
0
Pemasangan
0
Diblokir risiko
0
Perlu penyiapan
0
Produksi
0

Belum ada data hasil Agent. Eksekusi pertama dapat melaporkan keberhasilan, kebutuhan setup, blok risiko, kegagalan, atau tidak relevan melalui /api/agent/outcome.

Pasang

Tambahkan ke alur Agent

Gratis dan sumber terbuka. Tinjau laporan sebelum memasang pada Agent produksi.

Siklus pertumbuhan

Kit berbagi

X

Draf berbasis skenario untuk adhd, siap untuk posting manual di X.

Catatan kurator
adhd: Parallel divergent ideation — spawns N isolated generator agents under different cognitive fr...

42 stars

https://www.openagentskill.com/skills/darkroomengineering-adhd?ref=x
Buka draf X
Balasan opsional dengan perintah pemasangan
Listing + install path for adhd:
https://www.openagentskill.com/skills/darkroomengineering-adhd?ref=x

Install: npx skills add darkroomengineering/cc-settings --skill adhd
Buka draf balasan

Sumber listing

Diindeks Registry

Dapat diklaim

Listing ini diindeks dari sumber publik dan belum ditandai resmi hingga klaim pemelihara disetujui.

Diindeks oleh
Indeks komunitas OpenAgentSkill

Atribusi menautkan ke repositori publik atau profil kreator. Kreator dapat mengklaim listing untuk memperbarui sinyal kepemilikan.

Klaim skill ini

Klaim pemilik

Klaim listing skill ini

Listing Diindeks Registry ini dikaitkan dengan darkroomengineering, tetapi belum ditandai resmi. Klaim untuk menambahkan sinyal pemilik terverifikasi dan membuat pembaruan peluncuran, pemasangan, serta audit berikutnya lebih tepercaya.

Kit backlink kreator

Tambahkan badge bukti ke README Anda

Tampilkan listing kanonis, sinyal kepercayaan dan audit saat ini, serta bukti Agent-Proven nyata di tempat pengembang mengevaluasi repositori.

[![Listed on OpenAgentSkill](https://www.openagentskill.com/api/badge/darkroomengineering-adhd?metric=listed&label=Listed)](https://www.openagentskill.com/skills/darkroomengineering-adhd)
[![OpenAgentSkill Trust](https://www.openagentskill.com/api/badge/darkroomengineering-adhd?metric=trust&label=Trust)](https://www.openagentskill.com/skills/darkroomengineering-adhd)
[![OpenAgentSkill Audit](https://www.openagentskill.com/api/badge/darkroomengineering-adhd?metric=audit&label=Audit)](https://www.openagentskill.com/skills/darkroomengineering-adhd/audit)
[![Agent Proven](https://www.openagentskill.com/api/badge/darkroomengineering-adhd?metric=proven&label=Agent%20Proven)](https://www.openagentskill.com/skills/darkroomengineering-adhd)

Penulis

D

darkroomengineering

@darkroomengineering

Kecocokan platform

Sinyal kesehatan

Star GitHub
42
Skor kualitas
35/100
Push GitHub terakhir
20 Agu 2026
Petunjuk framework
Tidak diketahui
Tampilan OpenAgentSkill
3
Salinan pemasangan
0
Klik keluar
0

Sinyal komunitas

Bagikan apakah skill ini bermanfaat untuk alur kerja Agent Anda. Masukan gabungan meningkatkan peringkat dari waktu ke waktu.

Kepercayaan & keamanan

Hanya sandbox

65
  • Adopsi GitHub42 star GitHubPeriksa
  • Aktivitas star/fork42 star dan 3 fork; aktivitas issue tidak tersedia dalam metadata saat iniPeriksa
  • Pemeliharaan terbaru2 hari sejak pushLulus
  • Kejelasan lisensiMITLulus
  • Kelengkapan README/SKILL.mdMetadata memuat konteks penggunaan dan alur kerja yang cukupLulus
  • Risiko dependensi/runtimecommand execution surface, network or browser surfacePeriksa