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 Bevel-Software/Hexis --skill draft-responsegit clone --depth 1 https://github.com/Bevel-Software/HexisWrote 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/bevel-software/hexis/draft-response)<a href="https://agentmods.dev/skills/bevel-software/hexis/draft-response"><img src="https://agentmods.dev/badge/skills/bevel-software/hexis/draft-response/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/bevel-software/hexis/draft-response"><img src="https://agentmods.dev/badge/skills/bevel-software/hexis/draft-response.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 | $0.00053 | $0.03292 |
| Opus 5.5 | $0.00021 | $0.01317 |
| Sonnet 5.5 | $0.00011 | $0.00658 |
| Haiku 4.5 | $0.00005 | $0.00329 |
Grade A, and why
draft-response 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 6d 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
98% identical to draft-response — 18 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 — 417 lines — stays where its author put it; the contents beside it link to each section on GitHub.
draft-response
Names like
~~chator~~project trackermean whichever tool of that kind is connected: a tool in one of your Hexis plugins, or one your agent has itself. The knowledge base is this workspace's knowledge base in Hexis, plus any other docs tool that is connected. When a source is not connected, skip it and say what you could not check.
Draft a professional, customer-facing response tailored to the situation, customer relationship, and communication context.
Usage
Ask your agent for the draft-response skill by name, or just describe the job and it will pick the skill up. Give it: <context about the customer question, issue, or request>
Examples:
draft-response Acme Corp is asking when the new dashboard feature will shipdraft-response Customer escalation — their integration has been down for 2 daysdraft-response Responding to a feature request we won't be buildingdraft-response Customer hit a billing error and wants a resolution ASAP
Workflow
1. Understand the Context
Parse the user's input to determine:
- Customer: Who is the communication for? Look up account context if available.
- Situation type: Question, issue, escalation, announcement, negotiation, bad news, good news, follow-up
- Urgency: Is this time-sensitive? How long has the customer been waiting?
- Channel: Email, support ticket, chat, or other (adjust formality accordingly)
- Relationship stage: New customer, established, frustrated/escalated
- Stakeholder level: End user, manager, executive, technical, business
2. Research Context
Gather relevant background from available sources:
~~email:
- Previous correspondence with this customer on this topic
- Any commitments or timelines previously shared
- Tone and style of the existing thread
~~chat:
- Internal discussions about this customer or topic
- Any guidance from product, engineering, or leadership
- Similar situations and how they were handled
~~CRM (if connected):
- Account details and plan level
- Contact information and key stakeholders
- Previous escalations or sensitive issues
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.
- 6d ago First seen · 417 lines · 53 tokens per session scan A 83a207ab6776
draft-response is a skill published in the GitHub repository Bevel-Software/Hexis (115 stars, last pushed today), licensed Apache-2.0. It adds 53 tokens to every session and 3,292 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 98% identical to draft-response, differing in 18 lines, and is treated as a copy.
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