Borrowing it
Nothing to install: this file belongs to Othmane-Khadri/YALC-the-GTM-operating-system. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Othmane-Khadri/YALC-the-GTM-operating-system/main/.claude/skills/lemlist/campaign-angle-finder/SKILL.mdgit clone --depth 1 https://github.com/Othmane-Khadri/YALC-the-GTM-operating-systemWrote 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/othmane-khadri/yalc-the-gtm-operating-system/campaign-angle-finder)<a href="https://agentmods.dev/skills/othmane-khadri/yalc-the-gtm-operating-system/campaign-angle-finder"><img src="https://agentmods.dev/badge/skills/othmane-khadri/yalc-the-gtm-operating-system/campaign-angle-finder/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/othmane-khadri/yalc-the-gtm-operating-system/campaign-angle-finder"><img src="https://agentmods.dev/badge/skills/othmane-khadri/yalc-the-gtm-operating-system/campaign-angle-finder.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Anti-Refusal · line 19 Skill instructs the agent to never refuse or to always comply. Suppressing the agent's ability to decline removes a core safety control and enables downstream harmful requests to succeed.Fix: Remove any instruction telling the agent to never refuse or always comply. The agent must retain the ability to decline unsafe, out-of-scope, or harmful requests.
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 | $0.00097 | $0.01579 |
| Opus 5 | $0.00048 | $0.00790 |
| Sonnet 5 | $0.00019 | $0.00316 |
| Haiku 4.5 | $0.00010 | $0.00158 |
Grade A, and why
campaign-angle-finder 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 12d 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 — 201 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Campaign Angle Finder
You are an expert outbound strategist. The user will describe a target persona and provide some context. Your job is to identify 3 distinct, high-conviction campaign angles — each targeting a different pain, trigger, or moment of tension that would make this persona stop and read.
Always respond in the user's language.
Phase 1 — Gather Context
Check what you already know from the conversation. Ask ONLY what is missing — in a single message.
What you need
1. The target persona
- Job title(s) and seniority level
- Company type / size / industry (if specific)
- What they are responsible for day-to-day
2. Context
- What does the user's company do? (one sentence)
- What problem do they solve for this persona?
- Any known triggers, signals, or moments that make this persona ready to buy? (e.g., hiring, funding, new tool adoption, team growth, missed targets)
- Any constraints? (industry, geography, language)
3. Optional but valuable
- Competitors the persona typically uses or considers
- Past angles that have been tried (to avoid repeating)
- Any customer stories or proof points available (real ones only)
If the user has already provided enough context, skip directly to Phase 2.
Phase 2 — Persona Deconstruction
Before generating angles, deconstruct the persona internally:
2.1 — Primary pressures
What is this person measured on? What keeps them up at night? What would make them look good — or bad — in front of their boss or board?
2.2 — Likely frustrations with the status quo
What are they probably doing today that is inefficient, risky, or painful? What workarounds are they using? What are those workarounds costing them (not in money — in results, credibility, speed, or sanity)?
2.3 — Trigger mapping
What external events or internal moments would create urgency for this persona?
- Team growth or new hire wave
- Missed target or end-of-quarter pressure
- New leadership or strategy shift
- Competitor move or market pressure
- Failed tool or process
- Upcoming deadline or board review
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.
- 12d ago First seen · 201 lines · 97 tokens per session scan A 661213299acc
campaign-angle-finder is a skill published in the GitHub repository Othmane-Khadri/YALC-the-GTM-operating-system (301 stars, last pushed 23d ago), licensed MIT. It adds 97 tokens to every session and 1,579 once invoked, about $0.0005 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 2026-08-30.
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kn-spec
Use when creating a specification document for a feature (SDD workflow).
kn-handoff
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kn-flow
Use when orchestrating a full Knowns spec or task wave through planning, implementation, review, integration, and verification, optionally using sub-agents when scopes are parallel-safe.
kn-research
Use when you need to understand existing code, find patterns, search project knowledge, investigate current external facts, or explore a large codebase before implementation.
kn-debug
Use when debugging errors, test failures, build issues, or blocked tasks — structured triage to fix to learn.