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 customer-researchgit 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/customer-research)<a href="https://agentmods.dev/skills/bevel-software/hexis/customer-research"><img src="https://agentmods.dev/badge/skills/bevel-software/hexis/customer-research/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/customer-research"><img src="https://agentmods.dev/badge/skills/bevel-software/hexis/customer-research.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 | $0.00056 | $0.02194 |
| Opus 5.5 | $0.00022 | $0.00878 |
| Sonnet 5.5 | $0.00011 | $0.00439 |
| Haiku 4.5 | $0.00006 | $0.00219 |
Grade A, and why
customer-research 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
91% identical to customer-research — 10 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 — 251 lines — stays where its author put it; the contents beside it link to each section on GitHub.
customer-research
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.
Multi-source research on a customer question, product topic, or account-related inquiry. Synthesizes findings from all available sources with clear attribution and confidence scoring.
Usage
Ask your agent for the customer-research skill by name, or just describe the job and it will pick the skill up. Give it:
Workflow
1. Parse the Research Request
Identify what type of research is needed:
- Customer question: Something a customer has asked that needs an answer (e.g., "Does our product support SSO with Okta?")
- Issue investigation: Background on a reported problem (e.g., "Has this bug been reported before? What's the known workaround?")
- Account context: History with a specific customer (e.g., "What did we tell Acme Corp last time they asked about this?")
- Topic research: General topic relevant to support work (e.g., "Best practices for webhook retry logic")
Before searching, clarify what you're actually trying to find:
- Is this a factual question with a definitive answer?
- Is this a contextual question requiring multiple perspectives?
- Is this an exploratory question where the scope is still being defined?
- Who is the audience for the answer (internal team, customer, leadership)?
2. Search Available Sources
Search systematically through the source tiers below, adapting to what is connected. Don't stop at the first result — cross-reference across sources.
Tier 1 — Official Internal Sources (highest confidence):
- knowledge base (this workspace's, in Hexis): product docs, runbooks, FAQs, policy documents
- ~~cloud storage: internal documents, specs, guides, past research
- Product roadmap (internal-facing): feature timelines, priorities
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 · 251 lines · 56 tokens per session scan A 17606d4a286f
customer-research is a skill published in the GitHub repository Bevel-Software/Hexis (115 stars, last pushed today), licensed Apache-2.0. It adds 56 tokens to every session and 2,194 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 91% identical to customer-research, differing in 10 lines, and is treated as a copy.
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