Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/dbinky/dbinky-skill-set/ralph-plannpx skills add dbinky/dbinky-skill-set --skill ralph-plangit clone --depth 1 https://github.com/dbinky/dbinky-skill-setWrote 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/dbinky/dbinky-skill-set/ralph-plan)<a href="https://agentmods.dev/skills/dbinky/dbinky-skill-set/ralph-plan"><img src="https://agentmods.dev/badge/skills/dbinky/dbinky-skill-set/ralph-plan.svg" alt="Measured on agentmods" 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 | $0.00043 | $0.01697 |
| Opus 5 | $0.00022 | $0.00848 |
| Sonnet 5 | $0.00009 | $0.00339 |
| Haiku 4.5 | $0.00004 | $0.00170 |
Grade A, and why
ralph-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 5d 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.
How it starts
The opening of the file, as written. The whole thing — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ralph Plan
Prepare a project for a ralph refinement run by setting up tracking documents and populating them based on the work scope.
Usage
/ralph-plan # Scope = changes in current branch vs main
/ralph-plan PR #123 # Scope = changes in a specific PR
/ralph-plan "the new auth system" # Scope = user-described body of work
Process
Follow each phase in order. Do not skip phases.
Phase 1: Define Scope
Parse the user's arguments:
-
No arguments: Scope is changes in the current branch compared to the default branch. Run:
git log --oneline $(git merge-base HEAD main)..HEAD git diff --name-only $(git merge-base HEAD main)..HEADIf no divergence from main (i.e., we ARE on main or no commits ahead), ask: "You're on the default branch with no divergent commits. What should the scope be?"
-
PR number (e.g.,
#123or123): Fetch the PR diff:gh pr diff 123 gh pr view 123 --json title,body -
Free text description: Use the description as scope context. Still run
git diff --name-onlyagainst main to find changed files if any exist.
Store the result as SCOPE — a description of what's being reviewed plus the list of changed files.
Phase 2: Archive Previous Documents
Check for existing files:
RALPH.mddocs/reference/gaps-identified.mddocs/reference/focus-areas.md
If none exist: Skip to Phase 3.
If any exist:
- Determine today's date as
YYYY-MM-DD. - Determine the intra-day plan number — count today's existing backups (using one representative file type so the count is robust regardless of how many files each backup contains) and add 1:
If zero exist, the plan number is 1.echo $(( $(ls docs/reference/YYYY-MM-DD-historical-focus-areas-*.md 2>/dev/null | wc -l) + 1 )) - For each existing file, move (rename) it — do NOT copy it. The original must no longer exist at its working-tree location afterward:
RALPH.md→docs/reference/YYYY-MM-DD-historical-RALPH-{plan#}.mdgaps-identified.md→docs/reference/YYYY-MM-DD-historical-gaps-identified-{plan#}.mdfocus-areas.md→docs/reference/YYYY-MM-DD-historical-focus-areas-{plan#}.md
- Report: "Archived existing tracking docs as plan #{plan#} for {date}."
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 5d ago First seen · 173 lines · 43 tokens per session scan A db961e225a55
ralph-plan is a skill published in the GitHub repository dbinky/dbinky-skill-set (5 stars, last pushed 2mo ago), licensed MIT. It adds 43 tokens to every session and 1,697 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
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…
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…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…
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…