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 indranilbanerjee/digital-marketing-pro --skill signal-minegit clone --depth 1 https://github.com/indranilbanerjee/digital-marketing-proWrote 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/indranilbanerjee/digital-marketing-pro/signal-mine)<a href="https://agentmods.dev/skills/indranilbanerjee/digital-marketing-pro/signal-mine"><img src="https://agentmods.dev/badge/skills/indranilbanerjee/digital-marketing-pro/signal-mine/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/indranilbanerjee/digital-marketing-pro/signal-mine"><img src="https://agentmods.dev/badge/skills/indranilbanerjee/digital-marketing-pro/signal-mine.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 | $0.00154 | $0.00946 |
| Opus 5 | $0.00077 | $0.00473 |
| Sonnet 5 | $0.00031 | $0.00189 |
| Haiku 4.5 | $0.00015 | $0.00095 |
Grade A, and why
signal-mine 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 5d 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.
/digital-marketing-pro:signal-mine
The intelligence layer between "interesting" and "ours to say". Raw input comes from anywhere — a newsletter, a Reddit thread, three competitor posts, notes from yesterday's sales calls. The output is only the angles this brand has standing to make, each mapped to a pillar, with everything else explicitly dropped.
The mapping is the value. Any model can turn news into generic content ideas; the discipline is refusing the ideas that do not serve this brand's authority.
Inputs
- The dump — pasted material, in any shape. More is fine; this skill's job is triage.
- The brand profile — pillars, audience, positioning, competitors from
~/.claude-marketing/brands/{slug}/. No profile → stop: signal-mining without pillars produces trend-chasing, which is the exact failure mode this skill exists to prevent. Run /digital-marketing-pro:brand-setup first.
Process
- Split the dump into discrete signals (a claim, an event, a sentiment, a number, a competitor move).
- For each signal, ask the standing question: does this brand have something to say here that its audience would rather hear from it than from anyone else? Pillar fit is necessary but not sufficient — authority fit decides.
- For signals that pass: name the angle (the brand's specific take, not a summary of the signal), the pillar, a format, and a timeliness window.
- For signals that fail: list them as dropped, with the reason. This list is half the deliverable — it is the record of discipline, and the user may overrule it with context you lack.
Output structure
# Signal mine — {brand}, {date}
## Angles ({n})
### A1. [The angle — the take, not the topic]
**From signal:** [one-line source reference]
**Pillar:** [brand pillar] **Timeliness:** [act this week / evergreen / expires ~date]
**Format:** [post / article / newsletter section / campaign hook]
**Why this brand:** [one sentence of standing — why this take is credibly ours]
## Dropped ({n})
- [signal] — [why: off-pillar / no standing / competitor's story to tell /
stale by the time we publish / compliance risk]
## Sourcing note
[Which signals carry claims that need verification before anything cites them —
route those through /digital-marketing-pro:verify-claims before drafting]
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.
- 5d ago First seen · 78 lines · 154 tokens per session scan A 0cbb03603bd1
signal-mine is a skill published in the GitHub repository indranilbanerjee/digital-marketing-pro (812 stars, last pushed 5d ago), licensed MIT. It adds 154 tokens to every session and 946 once invoked, about $0.0008 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 2026-09-07.
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