signal-mine

signal-mine is a skill for Claude Code from indranilbanerjee/digital-marketing-pro. It costs 154 tokens per session (946 once invoked), scanned A, original, MIT.

A research-triage tool that sorts news, social discussions, competitor actions, and sales notes into usable content angles. It keeps only ideas that fit the brand's subject areas and authority, and records what it rejects.

In plain words
What is it for?
Use it to turn raw external material into topic ideas, assign each idea to a content area, choose a format, and set a useful time window.
Why use it?
It reduces trend-chasing and generic ideas by explaining why each selected signal is relevant to the brand. It also makes discarded material visible instead of silently ignoring it.

Skill for Claude Code

Written for Claude Code: user-invocable in frontmatter. Also seen: reads .claude/ paths.

Part of the digital-marketing-pro plugin — 154 skills, 18 commands, 24 agents shipped together

Good fit Use it to turn raw external material into topic ideas, assign each idea to a content area, choose a format, and set a useful time window.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/indranilbanerjee/digital-marketing-pro/signal-mine
Install

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.

Any agent
npx skills add indranilbanerjee/digital-marketing-pro --skill signal-mine
Clone the repo
git clone --depth 1 https://github.com/indranilbanerjee/digital-marketing-pro

Made for: Claude Code.

Or install digital-marketing-pro, the plugin that ships this one along with the rest of its 154 skills, 18 commands, 24 agents.

Wrote 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.

agentmods badge for signal-mine

README.md
[![agentmods](https://agentmods.dev/badge/skills/indranilbanerjee/digital-marketing-pro/signal-mine/github.svg)](https://agentmods.dev/skills/indranilbanerjee/digital-marketing-pro/signal-mine)
Your own site
<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.

agentmods 80×15 button for signal-mine

Your own site · 80×15
<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>
Per session 154 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 946 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 5d ago against content hash 0cbb03603bd1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

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.

skills/signal-mine/SKILL.md · 78 lines

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

  1. Split the dump into discrete signals (a claim, an event, a sentiment, a number, a competitor move).
  2. 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.
  3. 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.
  4. 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]

Read the full file on GitHub · 78 lines

Changes

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.

  1. 5d ago First seen · 78 lines · 154 tokens per session scan A 0cbb03603bd1

Subscribe to this mod's changes

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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