본문으로 건너뛰기
cccskills
무료GitHub에 공개

omos-plan

Plan one OpenSpec change through a coverage interview, codebase research, and evidence-based challenge of key decisions. Agent roles draft and critique the artifacts, followed by mechanical CLI validation, so the user can review a complete plan before implementation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

원문원문 설명 보기

Plan an OpenSpec change via $oh-my-openspec:omos-plan — coverage interview, parallel research, adversarial grill, agent-drafted artifacts, critique loop, mechanical CLI validation. Invoke via $oh-my-openspec:omos-plan.

hashgraph-online/awesome-codex-plugins스타 1,422(GitHub 1,422 + cccskills 0)

실행 점수 미검증

설치 방법 보기

이럴 때 유용합니다

  • Planning one focused OpenSpec change
  • Finding missing requirements and constraints
  • Researching existing code and project conventions
  • Validating planning artifacts before implementation

포함된 파일(1)

  • SKILL.md7.8 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Codex host adaptation (generated from skills/omos-plan/SKILL.md — source of truth stays there):

  • Dispatch roles with spawn_agent / send_input / wait_agent / close_agent. Subagents are asynchronous (default up to 6 concurrent threads), so a wave is one batch of spawn_agent calls followed by wait_agent collection — never poll.
  • openspec_validate is provided by this plugin's bundled MCP server as mcp__openspec__openspec_validate — call it with cwd set to your session's project directory (the change filter optional); the VALID/INVALID/UNAVAILABLE/ERROR one-look report format is identical to OpenCode.
  • This skill is invoked as a $oh-my-openspec:omos-plan mention (or picked from /skills). There is no argument substitution: arguments arrive as plain text in the user's message after the mention — read them from there; when absent, follow this skill's elicitation steps.
  • Roles run from ~/.codex/agents/omos-*.toml. If spawn_agent reports an unknown agent, stop and tell the user to run $oh-my-openspec:omos-setup once.

omos-plan

Turn the user's request into one complete, validated OpenSpec change under openspec/changes/<change-id>/. The orchestrator dispatches, never drafts — all artifact writing is done by role subagents. You never run git write commands: the user reviews files and decides what happens to them.

Flow

1. Preconditions

  • Check the CLI: call openspec_validate once. UNAVAILABLE → offer to install it now: run npm install -g @fission-ai/openspec (or brew install openspec on macOS) — a global install is a system change, so proceed only on an explicit yes. Installed → re-check and continue. Declined → offer to continue critic-only (non-mechanical validation) — their explicit yes required.
  • Check the project: openspec/ directory must exist. Missing → ask the user for consent, then run openspec init --tools none (project artifacts only; the plugin already provides every OpenSpec skill — never re-init tool files). User declines → stop.

2. Scope check

One change per run. If the request spans independent capabilities, produce a capability map (<name>: <one line> — depends on: <names|none>) and ask the user which capability to plan first.

3. Coverage interview

Keep an internal coverage map over six categories — Outcome + scenarios / Constraints + compat / Data + integrations / Failure + edge / Out of scope / Success metric — each Clear / Partial / Missing from the request text. Ask about at most 5 questions per round, ordered by Impact × Uncertainty (Missing categories first), each with a recommended answer:

  • Outcome: what the user observes when this is done.
  • Why now, and what "good" looks like (these become spec scenarios).
  • Constraints: platforms, libraries, performance, compatibility.
  • Out of scope: what this change must not touch.
  • Capability name(s) the behavior belongs to.

Skip questions the request already answers. Every question defines its terms with a concrete example or an either/or gloss; when the user signals non-understanding, in any language, restate the question with the gloss before recording an answer as ASSUMPTION:. Label anything the user leaves implicit ASSUMPTION: — the planner seeds these into the artifacts.

4. Research

Dispatch omos-researcher subagents in parallel — one per unknown area (codebase region, existing capability, conventions). Wait for every report. Every Unknown a read-only local command can answer (<binary> --help, a no-arg subcommand that performs no action) is re-dispatched to a researcher with a PROBE: line; no probe-resolvable Unknown survives into the §6 playback. Feed facts into the next steps; surface their Unknowns: questions in the following interview round.

5. Grill (1–3 rounds, up to 5)

Adversarial pass over the user's answers — the point is to break weak intent before it becomes paper.

  • Every attack must cite evidence: a research fact (path:line) or the user's own words. No invented what-ifs; an attack you cannot ground is dropped.
  • Attack checklist per material claim: alternative ("why not the existing X?"), edge/failure case, "what would make this decision wrong", scope-reduction pressure, scenario prioritization ("which two would you still ship without?").
  • Normally 1–3 rounds; up to 5 only when the change is large-scale — multiple capabilities in the map, compatibility/migration risk, or the user calls it big. At most 3 attacks per claim per round.
  • A round that produces no grounded attack ends the grill — intensity is set by what the evidence challenges, not by a quota.
  • The user may end the grill at any time with "enough".
  • Saturation (grill is done when all three hold): no category of the §3 coverage map is Missing; every vague adjective is pinned to a metric ("fast" → fast = how much, measured where?); and the last round produced no new grounded attack.
  • Each risk the user dismisses is recorded as REJECTED-RISK: <risk> — <their reason or "no reason given">. The grill does not override the user — it makes the dismissal visible.

6. Playback gate

Restate intent in seven lines — Outcome / Why now / Success / Constraints / Out of scope / Rejected risks / Established — and get explicit confirmation before any file is written. Established: recites up to five decision-relevant research findings the user might re-ask, one per line, absences included (e.g. "X exposes no theme API").

7. Draft

Dispatch omos-planner with MODE: plan: the confirmed playback, research facts, assumptions, REJECTED-RISK: lines, and a proposed change id (kebab-case verb-ish noun). It writes proposal, spec deltas, design (when non-trivial), tasks.

8. Critique loop (≤3 rounds)

Dispatch omos-critic on the drafted change.

  • NEEDS-FIX → dispatch omos-planner with the exact BLOCKING list to revise; repeat.
  • Wait for the planner revision to report DONE (the role's Status line) before dispatching the next critic; never batch a critic with the revision whose files it reads.
  • CLEAN → continue.
  • After 3 rounds still NEEDS-FIX → present the open findings to the user and ask: accept them, run one final planner revise plus mechanical openspec_validate with no further critic, or stop. A final revise ending with INVALID output is fixed mechanically and re-validated until VALID — never waived, the next bullet holds at loop end; only editorial findings are acceptable by user choice.
  • Mechanical INVALID lines from the critic are always fixed first, never waived by you.

9. Approval

Present: change id, file list with one-line summaries, every ASSUMPTION: and REJECTED-RISK: line verbatim, validation result. Ask the user to confirm.

  • Confirmed → final report: files, gate output, the current branch read from a read-only git branch --show-current-style check or "no branch yet" (reporting only — not a §1 precondition, no branch creation), next step $oh-my-openspec:omos-apply <change-id>. Stop — do not implement in the same breath. Offered invocations are the plugin's $oh-my-openspec:omos-* skill mentions whenever one exists for the action; the upstream openspec CLI is offered only where the plugin has no equivalent.
  • Rejected → collect the fix list as one interview round, go to §7.

Guardrails

  • No file outside openspec/changes/<change-id>/ and openspec/specs/ is written by any dispatched role; project code is untouched in this command.
  • Never commit, push, or stage anything.
  • The user's confirmed playback, not chat history, is the drafting contract.

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

Plan worthwhile local tasks by checking dependencies, effects, resources, and platform boundaries, then execute the exact approved plan. It can use safe parallel work or suitable Apple-silicon backends when the project exposes them.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Speed up independent local build or test steps
  • Plan a task with several dependency-linked operations
  • Choose an Apple-silicon backend for supported numerical or media work
hashgraph-online/awesome-codex-plugins1.4천2026년 10월 27일 업데이트

add

무료

Record deferred engineering decisions and temporary workarounds in a debt registry, with context such as effort, ongoing cost, affected area, and payoff trigger. Entries receive short labels so they can be reviewed or dropped later.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Logging a TODO or unfinished implementation
  • Recording a temporary default or bypassed check
  • Tracking a swallowed error or loosened type
hashgraph-online/awesome-codex-plugins1.4천2026년 10월 28일 업데이트

Generate or compare AI agent code for LangChain, EINO, AutoGen, AgentScope, and CrewAI using framework-specific templates, API mappings, conventions, and project structures. Reference files include verification dates to help identify potentially outdated guidance.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Creating an agent project for a chosen framework
  • Comparing APIs across supported agent frameworks
  • Referencing framework-specific tool and memory patterns
hashgraph-online/awesome-codex-plugins1.4천2026년 10월 26일 업데이트

Investigate a reproducible bug, test failure, or unexpected page behavior, then make a narrowly scoped fix. The workflow calls for a regression test before changing code, verifies the fix, and reports remaining risks and evidence while avoiding unrelated refactoring or feature work.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Finding the cause of a failing test
  • Fixing an unexpected page or feature behavior
  • Adding a regression test before a minimal code change
hashgraph-online/awesome-codex-plugins1.4천2026년 10월 28일 업데이트

Build an AI agent project through six collaborative stages, from requirements and architecture to tools, prompts, code generation, and verification. Start framework-independent, then generate a runnable project for frameworks such as LangChain, EINO, AutoGen, AgentScope, or CrewAI.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Designing an AI agent from a business need
  • Generating a runnable agent project
  • Planning tools, prompts, and orchestration
hashgraph-online/awesome-codex-plugins1.4천2026년 10월 26일 업데이트

Audit a project or learning workflow for scope drift, conflicting plans, inconsistent names, and code quality concerns. The skill reads project files and code, then reports evidence, severity, and suggested next steps without changing files.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Checking whether project work has drifted from its agreed scope
  • Finding conflicting plans or inconsistent naming
  • Reviewing code against project decisions without editing it
hashgraph-online/awesome-codex-plugins1.4천2026년 10월 28일 업데이트

hashgraph-online의 스킬 모두 보기

이 스킬의 문제 신고