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/robroyhobbs/marketing-skillsnpx agentmods add skills/robroyhobbs/marketing-skills/positioning-anglesWrote 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/robroyhobbs/marketing-skills/positioning-angles)<a href="https://agentmods.dev/skills/robroyhobbs/marketing-skills/positioning-angles"><img src="https://agentmods.dev/badge/skills/robroyhobbs/marketing-skills/positioning-angles/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/robroyhobbs/marketing-skills/positioning-angles"><img src="https://agentmods.dev/badge/skills/robroyhobbs/marketing-skills/positioning-angles.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 | $0.00134 | $0.05929 |
| Opus 5 | $0.00067 | $0.02965 |
| Sonnet 5 | $0.00027 | $0.01186 |
| Haiku 4.5 | $0.00013 | $0.00593 |
Grade A, and why
positioning-angles 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 — 768 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Positioning & Angles
The same product can sell 100x better with a different angle. Not a different product. Not better features. Just a different way of framing what it already does.
This skill finds those angles.
Brand memory integration
Read ./brand/ per _system/brand-memory.md
Reads: audience.md, competitors.md (if they exist)
On invocation, check for ./brand/ and load available context:
-
Check for
./brand/positioning.md-- if it exists, this is an update session:- Read the existing positioning file
- Display the current primary angle and any saved alternatives
- Ask: "You already have positioning on file. Do you want to refine it with fresh data, or start from scratch?"
- "Refine" -- load existing angles, run competitive search for new data, suggest adjustments to current positioning based on what has changed in the market
- "Start fresh" -- run the full process below as if no positioning exists
-
Load
audience.md(if exists):- Use audience segments, pain points, and language patterns to inform angle generation
- Show: "I see your audience profile -- [brief summary]. Using that to shape angles."
-
Load
competitors.md(if exists):- Use known competitors as starting seeds for the competitive web search step
- Show: "I found [N] competitors in your brand memory. Starting search from there."
-
Load
voice-profile.md(if exists):- Use voice DNA to ensure angle language matches brand tone
- Show: "Your voice is [tone summary]. Angles will match that register."
-
If
./brand/does not exist:- Skip brand loading entirely. Do not error.
- Note in opening message: "No brand profile found — this skill works standalone. I'll ask what I need. You can run /start-here or /brand-voice later to unlock personalization."
The core job
When someone asks about positioning or angles, the goal is not to find THE answer. It is to surface multiple powerful options they can choose from.
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 768 lines · 134 tokens per session scan A 752d24dc3898
positioning-angles is a skill published in the GitHub repository robroyhobbs/marketing-skills (5 stars, last pushed 5mo ago), licensed MIT. It adds 134 tokens to every session and 5,929 once invoked, about $0.0007 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…