القائمة
Scan ALL available skills before any non-trivial request. Prevents skill blindness, tunnel vision, and wrong-skill selection. Entry point for all skill-assisted work.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Build automation scripts and pipelines that use coding-agent CLIs (Claude Code, Codex, Gemini CLI, GitHub Copilot CLI) in headless/non-interactive mode as the AI engine, or delegate work to cloud agents (`gh agent-task`) that open pull requests asynchronously. Use this skill whenever the user wants to write a shell script, CI job, cron task, batch processor, webhook handler, or any automation that shells out to `claude`, `codex`, `gemini`, `copilot`, or `gh agent-task` — single-turn prompts, multi-turn agentic loops, parallel fan-out across files/folders, structured JSON outputs consumed by downstream tools, or cloud-delegated tasks that produce PRs. Trigger on phrases like "script that uses Claude", "automate with Claude Code", "headless Claude", "batch process files with an LLM", "pipeline with codex exec", "gemini -p", "copilot --autopilot", "gh agent-task create", "GitHub Action that calls Claude", "cron job to review PRs", "agent loop in bash", "dispatch an agent task to open a PR", "fleet-wide agent-tas
Apply causal inference whenever the user is interpreting metrics, debugging system behavior, reading A/B test results, or trying to understand whether an observed change was caused by an action or by something else. Triggers on phrases like "X caused Y", "since we deployed this, metrics changed", "the A/B test showed a lift", "why did this metric move?", "is this correlation or causation?", "we changed X and Y improved", "how do we know this worked?", "the data shows…", or any situation where conclusions are being drawn from observational data. Also trigger before any decision based on metric interpretation — confusing correlation with causation leads to interventions that don't work and misattribution of credit. Never assume causation without applying this skill.
Apply ethical reasoning whenever the user faces a decision, design, or action with moral implications — especially when someone could be harmed, rights could be violated, or values are in tension. Triggers on phrases like "is this the right thing to do?", "what are the ethical implications?", "who could this harm?", "should we build this?", "is this fair?", "what are our obligations?", "value trade-off", "responsible AI". Use proactively when reviewing any high-stakes decision, product design affecting vulnerable populations, or action where the beneficiaries and those bearing costs are different groups.
Apply execution-planning whenever the user has made a decision and needs to turn it into action — decomposing work, sequencing tasks, estimating timelines, and assigning ownership. Triggers on phrases like "how do we execute this?", "break this into tasks", "what's the project plan?", "create a roadmap", "what are the dependencies?", "who does what by when?", "how long will this take to build?". Use proactively after decision-synthesis or architecture-evaluation produces a committed decision that requires coordinated implementation.
Apply experimental-design whenever the user needs to test a hypothesis, validate an assumption, or determine whether something actually works. Triggers on phrases like "how do we test this?", "design an experiment", "what would prove this?", "set up an A/B test", "how do we validate this hypothesis?", "what's the right control?", "is this result significant?", "what sample size do we need?". Use proactively when decisions rest on untested assumptions — designing the test before collecting data prevents post-hoc rationalization.
Apply fairness auditing whenever the user describes a system, algorithm, policy, or process that allocates outcomes across groups and wants to know whether it is equitable. Triggers on phrases like "is this fair?", "disparate impact", "bias in the system", "does this discriminate?", "algorithmic fairness", "who's disadvantaged by this?", "equitable outcomes". Use proactively when reviewing any allocation mechanism, scoring system, or automated decision pipeline that affects people differently based on group membership.
| name | skill-router |
| description | Scan ALL available skills before any non-trivial request. Prevents skill blindness, tunnel vision, and wrong-skill selection. Entry point for all skill-assisted work. |
Attention-recovery and composition layer. Does NOT perform tasks — scans, matches, plans. All work done by routed skills.
Request: [one-sentence restatement]
Deliverable: [artifact or answer]
Secondary needs: [implicit — analysis, validation, formatting, org dynamics]
Domain: [technical / creative / analytical / organizational / mixed]
Complexity: [simple (1 skill) / composed (2-3) / orchestrated (4+)]
Rules: analysis + production = two skill needs. Decision = reasoning + output. Organizational dynamics (adoption, buy-in) = separate need even if unstated.
Read EVERY skill description. Do not stop after first match.
Score each: PRIMARY (core intent, output worse without it) · SUPPORTING (secondary need, quality boost) · IRRELEVANT
Zero PRIMARY matches = you skimmed. Re-read.
Primary: [skill]: [which intent component]
Supporting: [skill]: [what quality dimension]
Excluded: [skill]: [why not, non-obvious only]
| Intent shape | Pattern |
|---|---|
| Pure analysis/diagnosis/decision | SINGLE or ORCHESTRATED |
| Pure production (write/create/build) | SINGLE — match output format |
| Analysis → production | PIPELINE — analytical skill → production skill |
| Multi-lens review/audit | PARALLEL → CONVERGE — different quality dimensions |
| Compression/summarization | SINGLE or PIPELINE (chain if large input) |
| Ideation/brainstorming | SINGLE or PARALLEL creative skills |
| File transformation | SINGLE — match target format |
| Complex multi-faceted | ORCHESTRATED — split analysis + production phases |
SKILL ROUTER — PLAN
Intent: [one-line]
Pattern: [from table]
Skills: [ordered list with roles]
---
Executing Step 1: [skill-name]
Read first skill's SKILL.md, begin. Pipeline: carry output forward. Parallel: execute sequentially then synthesize.
Skip for: greetings, factual questions, follow-ups mid-execution, user naming a specific skill.
Always invoke for: new substantive requests, temptation to answer from raw capability when skills exist, multi-domain requests.
Mid-execution: if a skill was missed — pause, re-run Step 2, amend, resume.