Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/bricerising/enterprise-software-playbooknpx agentmods add skills/bricerising/enterprise-software-playbook/intelWrote 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/bricerising/enterprise-software-playbook/intel)<a href="https://agentmods.dev/skills/bricerising/enterprise-software-playbook/intel"><img src="https://agentmods.dev/badge/skills/bricerising/enterprise-software-playbook/intel.svg" alt="Measured on agentmods" 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 | $0.00078 | $0.03868 |
| Opus 5 | $0.00039 | $0.01934 |
| Sonnet 5 | $0.00016 | $0.00774 |
| Haiku 4.5 | $0.00008 | $0.00387 |
Grade A, and why
intel 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.
How it starts
The opening of the file, as written. The whole thing — 373 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Intel (Intelligence Briefs)
Overview
Produce focused intelligence briefs on a topic by querying the intel CLI against locally collected feeds (RSS, HackerNews, EDGAR). Briefs combine trending signals, full-text search hits, and topic breakdowns into a concise, evidence-backed summary an agent or human can act on.
Use this skill when you need current signal on a technology, vendor, standard, or industry trend — or when you need to present signals to a specific audience.
Success looks like: a brief with ranked signals, source citations, and a clear "so what" tailored for the target audience — readable in under 2 minutes and actionable without needing to parse raw data.
Prerequisites
-
Build the tool:
cd tools/intelligence && npm install && npm run build -
Make
intelavailable on PATH:npm link # from tools/intelligence/ -
Create a config file:
mkdir -p ~/.config/intel ~/.local/share/intel cp config/feeds.example.yaml ~/.config/intel/config.yaml # Edit ~/.config/intel/config.yaml to customize feeds -
Seed the database (first run):
intel collect --once -
Install the collector as a background service so data stays fresh:
./service/install.sh # macOS (launchd) / Linux (systemd)This installs a LaunchAgent (macOS) or systemd user unit (Linux) that starts on login and restarts on crash. Verify it's running:
# macOS launchctl print gui/$(id -u)/com.intel.collector tail -f ~/Library/Logs/intel-collector.log # Linux systemctl --user status intel-collector journalctl --user -u intel-collector -fTo uninstall:
./service/install.sh uninstall -
Verify:
intel stats— checkevents_total > 0andnewest_eventis recent.
Inputs / Outputs
Inputs: Topic scope (what to research); audience type (practitioner/executive/engineering/decision/digest/architecture); time window.
Outputs: Audience-formatted intelligence brief with ranked signals, source citations, and "so what." Consumed by forecast (as data source), plan (as context), architecture (as ecosystem evidence).
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 · 373 lines · 78 tokens per session scan A 3d384a033f34
intel is a skill published in the GitHub repository bricerising/enterprise-software-playbook (7 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 78 tokens to every session and 3,868 once invoked, about $0.0004 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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