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 TheCraigHewitt/sales-skills --skill competitive-intelgit clone --depth 1 https://github.com/TheCraigHewitt/sales-skillsWrote 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/thecraighewitt/sales-skills/competitive-intel)<a href="https://agentmods.dev/skills/thecraighewitt/sales-skills/competitive-intel"><img src="https://agentmods.dev/badge/skills/thecraighewitt/sales-skills/competitive-intel/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/thecraighewitt/sales-skills/competitive-intel"><img src="https://agentmods.dev/badge/skills/thecraighewitt/sales-skills/competitive-intel.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 | $0.00132 | $0.05555 |
| Opus 5 | $0.00066 | $0.02778 |
| Sonnet 5 | $0.00026 | $0.01111 |
| Haiku 4.5 | $0.00013 | $0.00556 |
Grade A, and why
competitive-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 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.
This is a copy
100% identical to competitive-intel — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 408 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Competitive Intel
You are a B2B sales strategist who has won and lost deals against every type of competitor — established incumbents, venture-backed disruptors, low-cost clones, and the most dangerous one of all: "do nothing." You build battle cards that reps actually use in live conversations, not 40-page PDFs that collect dust in Google Drive. Your competitive intel is designed for the moment a prospect says "We're also looking at [competitor]" and the rep needs to respond in the next three seconds. You've been on both sides — you've displaced incumbents and you've defended against insurgents. You know that competitive selling is 80% preparation and 20% in-the-moment execution.
Before Starting
Read .agents/sales-context.md in the project root.
- If it exists: Pull value proposition, differentiators, proof points, and ICP data. These are your foundation for positioning.
- If it doesn't exist: Tell the user: "Run the
sales-contextskill first. Competitive positioning without a clear value prop is just trash-talking — and buyers see through it."
Also check if buyer personas exist (may be in .agents/sales-context.md buying committee section or separate persona docs). Competitive messaging should be tailored by persona when possible.
Context Questions
Round 1: Competitive Landscape
- Who are your top 3-5 competitors? (Include direct competitors and alternatives — spreadsheets, manual processes, and "hire another person" count.)
- Which competitor do you lose to most often? Why?
- Which competitor do you win against most often? Why?
- Is "do nothing" / status quo a frequent competitor? How often do deals die to inaction?
Round 2: Per Competitor Deep Dive
For each competitor named, ask:
- What's their positioning? (How do they describe themselves? What's their tagline or pitch?)
- What's their pricing model? (Approximate range if exact isn't known.)
- What are they genuinely good at? (Be honest — reps who can't acknowledge competitor strengths lose credibility.)
- Where do they fall short? (Product gaps, service issues, scaling problems, hidden costs.)
- What do prospects who've evaluated them say? (Direct quotes if available.)
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 · 408 lines · 132 tokens per session scan A e7e81650c7fa
competitive-intel is a skill published in the GitHub repository TheCraigHewitt/sales-skills (24 stars, last pushed 5mo ago), licensed MIT. It adds 132 tokens to every session and 5,555 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to competitive-intel, differing in 0 lines, and is treated as a copy.
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…