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 skills add naimkatiman/continuous-improvement --skill idea-refinegit clone --depth 1 https://github.com/naimkatiman/continuous-improvementWrote 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/naimkatiman/continuous-improvement/idea-refine)<a href="https://agentmods.dev/skills/naimkatiman/continuous-improvement/idea-refine"><img src="https://agentmods.dev/badge/skills/naimkatiman/continuous-improvement/idea-refine/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/naimkatiman/continuous-improvement/idea-refine"><img src="https://agentmods.dev/badge/skills/naimkatiman/continuous-improvement/idea-refine.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 | $0.00035 | $0.01811 |
| Opus 5.5 | $0.00014 | $0.00724 |
| Sonnet 5.5 | $0.00007 | $0.00362 |
| Haiku 4.5 | $0.00003 | $0.00181 |
Grade A, and why
idea-refine 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
89% identical to idea-refine — 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 — 179 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Idea Refine
Refines raw ideas into sharp, actionable concepts worth building through structured divergent and convergent thinking.
How It Works
- Understand & Expand (Divergent): Restate the idea, ask sharpening questions, and generate variations.
- Evaluate & Converge: Cluster ideas, stress-test them, and surface hidden assumptions.
- Sharpen & Ship: Produce a concrete markdown one-pager moving work forward.
Usage
This skill is primarily an interactive dialogue. Invoke it with an idea, and the agent will guide you through the process.
# Optional: Initialize the ideas directory
bash /mnt/skills/user/idea-refine/scripts/idea-refine.sh
Trigger Phrases:
- "Help me refine this idea"
- "Ideate on [concept]"
- "Stress-test my plan"
Output
The final output is a markdown one-pager saved to docs/ideas/[idea-name].md (after user confirmation), containing:
- Problem Statement
- Recommended Direction
- Key Assumptions
- MVP Scope
- Not Doing list
Detailed Instructions
You are an ideation partner. Your job is to help refine raw ideas into sharp, actionable concepts worth building.
Philosophy
- Simplicity is the ultimate sophistication. Push toward the simplest version that still solves the real problem.
- Start with the user experience, work backwards to technology.
- Say no to 1,000 things. Focus beats breadth.
- Challenge every assumption. "How it's usually done" is not a reason.
- Show people the future — don't just give them better horses.
- The parts you can't see should be as beautiful as the parts you can.
Process
When the user invokes this skill with an idea ($ARGUMENTS), guide them through three phases. Adapt your approach based on what they say — this is a conversation, not a template.
Phase 1: Understand & Expand (Divergent)
Goal: Take the raw idea and open it up.
- Restate the idea as a crisp "How Might We" problem statement. This forces clarity on what's actually being solved.
What ships with it
4 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.
- 1mo ago First seen · 179 lines · 35 tokens per session scan A 82cd83f2bd16
idea-refine is a skill published in the GitHub repository naimkatiman/continuous-improvement (9 stars, last pushed 1mo ago), licensed MIT. It adds 35 tokens to every session and 1,811 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 89% identical to idea-refine, differing in 29 lines, and is treated as a copy.
Other skills, from other repositories
opensrc
Fetch dependency source code to give AI agents deeper implementation context. Use when the agent needs to understand how a library works internally, read source code for a package, fetch implementation details for a dependency, or explore how an npm/PyPI/crates.io package is built. Triggers include "fetch source for"…
nopus-configure
Configure nopus complexity sensitivity, extra-simple rewrites, rewrite evidence, and Pi response hiding for this user.
agentproto-llm-endpoint
Use the local LLM endpoint proxy (localhost:18090) — or your own gated public deployment — to route Claude Code / Claude SDK through custom providers (OpenRouter, Moonshot, Groq, ZAI) via an Anthropic-compatible gateway. Covers adapter-specific behaviors, auth patterns, proxy codenames, and common failure modes.
agentpush
Bridge an imported agentpush MCP server (Telegram, WhatsApp, etc.) with live agentproto sessions via the daemon's transmitter subsystem: transmitmessage sends outbound and binds the recipient to a session, inboundwatcherstart polls agentpush for new messages, and inboundendpointcreate/POST /inbound(/:slug) route…
bureau
Drive Bureau — the browser stack's installable capability server: a stealth Firefox (Camofox) + daemon that exposes browser tools as MCP-over-HTTP on :8830, plus a CLI for saved browser identities (sessions), social capture / search, adapter health probes, declarative workflows, and Guilde connection. Use when working…
ap-workflows
Run multi-stage session pipelines with agentproto workflows — workflowstart with barrier-gated stages of concurrent steps, sessionRef to reuse earlier output, workflowstatus/cancel/retry, workflowrunfile for AIP-15 WORKFLOW.md, and workflowescalationresolve for human answers. Trigger when asked to pipeline agents, fan…