facts-refine

facts-refine is a skill for Claude Code, Codex from av/mi. It costs 68 tokens per session (1,360 once invoked), scanned A, original, no licence file.

A skill for managing @draft facts—unfinished project statements—and turning them into precise @spec facts ready for implementation.

In plain words
What is it for?
Refine requirements, clarify facts with the user, improve labels, and prepare facts for implementation.
Why use it?
It resolves unclear wording, missing details, and contradictions before coding starts.

Skill for Claude CodeCodex

View the source file av/mi
Install

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.

agentmods
npx agentmods add skills/av/mi/facts-refine
Any agent
npx skills add av/mi --skill facts-refine
Clone the repo
git clone --depth 1 https://github.com/av/mi

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for facts-refine

README.md
[![agentmods](https://agentmods.dev/badge/skills/av/mi/facts-refine.svg)](https://agentmods.dev/skills/av/mi/facts-refine)
Your own site
<a href="https://agentmods.dev/skills/av/mi/facts-refine"><img src="https://agentmods.dev/badge/skills/av/mi/facts-refine.svg" alt="Measured on agentmods" height="20"></a>
Per session 68 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,360 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00068 $0.01360
Opus 5 $0.00034 $0.00680
Sonnet 5 $0.00014 $0.00272
Haiku 4.5 $0.00007 $0.00136

Measured 4d ago against content hash 9a9272153548, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

facts-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 4d 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.

.agents/skills/facts-refine/SKILL.md · 140 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

Changes

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.

  1. 4d ago First seen · 140 lines · 68 tokens per session scan A 9a9272153548

Subscribe to this mod's changes

facts-refine is a skill published in the GitHub repository av/mi (102 stars, last pushed 2mo ago), with no licence file. It adds 68 tokens to every session and 1,360 once invoked, about $0.0003 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 2026-08-30.

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