Borrowing it
Nothing to install: this file belongs to Orinks/AccessiWeather. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Orinks/AccessiWeather/main/.codex/skills/plan/SKILL.mdgit clone --depth 1 https://github.com/Orinks/AccessiWeatherWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/orinks/accessiweather/plan)<a href="https://agentmods.dev/skills/orinks/accessiweather/plan"><img src="https://agentmods.dev/badge/skills/orinks/accessiweather/plan/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/orinks/accessiweather/plan"><img src="https://agentmods.dev/badge/skills/orinks/accessiweather/plan.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00012 | $0.04507 |
| Opus 5.5 | $0.00005 | $0.01803 |
| Sonnet 5.5 | $0.00002 | $0.00901 |
| Haiku 4.5 | $0.00001 | $0.00451 |
Grade A, and why
plan scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
88% identical to plan — 29 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 278 lines — stays where its author put it; the contents beside it link to each section on GitHub.
<Use_When>
- User wants to plan before implementing -- "plan this", "plan the", "let's plan"
- User wants structured requirements gathering for a vague idea
- User wants an existing plan reviewed -- "review this plan",
--review - User wants multi-perspective consensus on a plan --
--consensus, "ralplan" - Task is broad or vague and needs scoping before any code is written </Use_When>
<Do_Not_Use_When>
- User wants autonomous end-to-end execution -- use
autopilotinstead - User wants to start coding immediately with a clear task -- use
ralphor delegate to executor - User asks a simple question that can be answered directly -- just answer it
- Task is a single focused fix with obvious scope -- skip planning, just do it </Do_Not_Use_When>
<Why_This_Exists> Jumping into code without understanding requirements leads to rework, scope creep, and missed edge cases. Plan provides structured requirements gathering, expert analysis, and quality-gated plans so that execution starts from a solid foundation. The consensus mode adds multi-perspective validation for high-stakes projects. </Why_This_Exists>
<Execution_Policy>
- Auto-detect interview vs direct mode based on request specificity
- Ask one question at a time during interviews -- never batch multiple interview rounds into one question form
- Gather codebase facts via
exploreagent before asking the user about them - When session guidance enables
USE_OMX_EXPLORE_CMD, preferomx explorefor simple read-only repository lookups during planning; keep prompts narrow and concrete, and keep prompt-heavy or ambiguous planning work on the richer normal path and fall back normally ifomx exploreis unavailable. - Plans must meet quality standards: 80%+ claims cite file/line, 90%+ criteria are testable
- Implementation step count must be right-sized to task scope; avoid defaulting to exactly five steps when the work is clearly smaller or larger
- Consensus mode outputs the final plan by default; add
--interactiveto enable execution handoff - Consensus mode uses RALPLAN-DR short mode by default; switch to deliberate mode with
--deliberateor when the request explicitly signals high risk (auth/security, data migration, destructive/irreversible changes, production incident, compliance/PII, public API breakage) - Apply the shared workflow guidance pattern: outcome-first framing, concise visible updates for multi-step planning, local overrides for the active workflow branch, evidence-backed planning and validation expectations, explicit stop rules, and automatic continuation for safe reversible steps. Ask only for material, destructive, credentialed, external-production, or preference-dependent branches. </Execution_Policy>
Mode Selection
| Mode | Trigger | Behavior |
|---|---|---|
| Interview | Default for broad requests | Interactive requirements gathering |
| Direct | --direct, or detailed request |
Skip interview, generate plan directly |
| Consensus | --consensus, "ralplan" |
Planner -> Architect -> Critic loop until agreement with RALPLAN-DR structured deliberation (short by default, --deliberate for high-risk); outputs plan by default |
| Consensus Interactive | --consensus --interactive |
Same as Consensus but pauses for user feedback at draft and approval steps, then hands off to execution |
| Review | --review, "review this plan" |
Critic evaluation of existing plan |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 278 lines · 12 tokens per session scan A 34995d06426d
plan is a skill published in the GitHub repository Orinks/AccessiWeather (24 stars, last pushed 2d ago), licensed MIT. It adds 12 tokens to every session and 4,507 once invoked, about $0.0000 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 88% identical to plan, differing in 29 lines, and is treated as a copy.
Other skills, from other repositories
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chronicle
Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
component-fixtures
Use when creating or updating component fixtures for screenshot testing or their shared infrastructure, or when designing UI components to be fixture-friendly. Covers fixture file structure, theming, service setup, CSS scoping, async rendering, validation, and common pitfalls.