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 bmbouter/redhat-agents --skill customer-signal-aggregatorgit clone --depth 1 https://github.com/bmbouter/redhat-agentsWrote 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/bmbouter/redhat-agents/customer-signal-aggregator)<a href="https://agentmods.dev/skills/bmbouter/redhat-agents/customer-signal-aggregator"><img src="https://agentmods.dev/badge/skills/bmbouter/redhat-agents/customer-signal-aggregator/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/bmbouter/redhat-agents/customer-signal-aggregator"><img src="https://agentmods.dev/badge/skills/bmbouter/redhat-agents/customer-signal-aggregator.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 | $0.00029 | $0.00554 |
| Opus 5 | $0.00015 | $0.00277 |
| Sonnet 5 | $0.00006 | $0.00111 |
| Haiku 4.5 | $0.00003 | $0.00055 |
Grade A, and why
customer-signal-aggregator 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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.
When to Use
When the PM wants to understand what customers are asking for, what pain points keep recurring, or where demand is clustering.
Instructions
Read local/jira-workflow.md to understand issue types, labels, and components.
1. Define the search scope
Ask the PM:
- Area of interest: A specific feature area? Component? Epic? Or everything?
- Time period: Last quarter? Last 6 months? All time?
- Signal types: Bugs only? Feature requests? Support escalations? All?
2. Search broadly
Run multiple Jira queries to gather signals:
Recent bugs in the area:
project = <PROJECT> AND issuetype = Bug AND created >= "<start_date>" ORDER BY created DESC
Feature requests / tasks:
project = <PROJECT> AND issuetype in (Task, Story) AND created >= "<start_date>" ORDER BY created DESC
Issues with specific keywords (if the PM gave a topic):
project = <PROJECT> AND text ~ "<keywords>" ORDER BY created DESC
Read the summaries and descriptions to understand what each issue is actually about.
3. Identify themes
Group related issues by theme. A theme is a cluster of issues pointing at the same underlying need, even if they use different words.
For each theme, note:
- How many issues
- How many distinct reporters
- Severity distribution
- Whether any existing epics address it
- Whether it's getting better or worse over time
4. Present findings
## Customer Signal Analysis — <area> — <period>
### Top Themes
#### 1. [Theme name] (X issues, Y reporters)
- **Pattern**: [What customers are experiencing]
- **Examples**: ISSUE-123, ISSUE-456, ISSUE-789
- **Severity**: X Critical, Y Major, Z Normal
- **Existing coverage**: [Related epic or "none"]
- **Trend**: Growing / Stable / Declining
#### 2. [Theme name] (X issues, Y reporters)
...
### Signals Without a Clear Theme
- ISSUE-012 — [One-off request worth noting]
### Recommendations
- [Theme 1 warrants a new epic — no existing coverage]
- [Theme 2 is addressed by EPIC-XXX but progress is slow]
- [Theme 3 is declining — may resolve with upcoming release]
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.
- 9d ago First seen · 78 lines · 29 tokens per session scan A 658da03fac89
customer-signal-aggregator is a skill published in the GitHub repository bmbouter/redhat-agents (6 stars, last pushed 4d ago), licensed Apache-2.0. It adds 29 tokens to every session and 554 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 2026-08-31.
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