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 alivirgo/Major-AI-Skills --skill be-specific-instead-of-vaguegit clone --depth 1 https://github.com/alivirgo/Major-AI-SkillsWrote 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/alivirgo/major-ai-skills/be-specific-instead-of-vague)<a href="https://agentmods.dev/skills/alivirgo/major-ai-skills/be-specific-instead-of-vague"><img src="https://agentmods.dev/badge/skills/alivirgo/major-ai-skills/be-specific-instead-of-vague/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/alivirgo/major-ai-skills/be-specific-instead-of-vague"><img src="https://agentmods.dev/badge/skills/alivirgo/major-ai-skills/be-specific-instead-of-vague.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 | $0.00025 | $0.01001 |
| Opus 5 | $0.00013 | $0.00500 |
| Sonnet 5 | $0.00005 | $0.00200 |
| Haiku 4.5 | $0.00003 | $0.00100 |
Grade A, and why
be-specific-instead-of-vague 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 yesterday.
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 — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Be Specific Instead of Vague (The Precision Protocol) (AI Skill)
Overview
The quality of an AI's response is directly proportional to the constraints provided in the prompt. Vague prompts ("Write a blog post about productivity", "Fix my code") trigger the broadest, most generic probability distribution in the LLM, producing bland, predictable text.
The Precision Protocol uses the 5-Variable Specificity Formula to anchor the model to your exact intended context, eliminating 90% of back-and-forth revisions.
The 5-Variable Specificity Formula
┌─────────────────────────────────────────────────────────────┐
│ The 5-Variable Formula │
│ │
│ [ ROLE ] ──► Who is the AI speaking as? │
│ [ AUDIENCE ] ──► Who is reading / receiving this? │
│ [ GOAL ] ──► What exact outcome must be achieved? │
│ [ BOUNDARY ] ──► Length, format, and banned elements? │
│ [ CONTEXT ] ──► Key facts, data points, or constraints? │
└─────────────────────────────────────────────────────────────┘
Real-World Transformations: Vague vs. Specific
Example 1: Email Request to a Colleague
Vague (Low Precision)
❌ "Write an email asking for the sales numbers."
Result: AI writes a 4-paragraph corporate letter starting with "I hope this email finds you well in these busy times..."
Specific (Precision Formula Applied)
✅ "Write a 2-sentence Slack message to our sales lead (Dave) asking for the updated Q2 EMEA revenue spreadsheet by 3 PM today for the board prep meeting. Friendly but urgent tone."
Result: "Hey Dave, could you share the updated Q2 EMEA revenue spreadsheet by 3 PM today? Putting the final slides together for tomorrow's board prep."
Example 2: Code Refactoring
Vague
❌ "Make this Python script faster."
Result: AI adds comments, renames variables, or suggests generic multiprocessing libraries that don't fit the workload.
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.
- yesterday Changed · -11 tokens per session c7031a479427
- 7d ago First seen · 96 lines · 36 tokens per session scan A 859fb39b46ed
be-specific-instead-of-vague is a skill published in the GitHub repository alivirgo/Major-AI-Skills (1 stars, last pushed today), licensed MIT. It adds 25 tokens to every session and 1,001 once invoked, about $0.0001 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 2026-09-05.
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