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 gtmagents/gtm-agents --skill battlecard-librarygit clone --depth 1 https://github.com/gtmagents/gtm-agentsWrote 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/gtmagents/gtm-agents/battlecard-library)<a href="https://agentmods.dev/skills/gtmagents/gtm-agents/battlecard-library"><img src="https://agentmods.dev/badge/skills/gtmagents/gtm-agents/battlecard-library/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/gtmagents/gtm-agents/battlecard-library"><img src="https://agentmods.dev/badge/skills/gtmagents/gtm-agents/battlecard-library.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 | $0.00017 | $0.00266 |
| Opus 5 | $0.00009 | $0.00133 |
| Sonnet 5 | $0.00003 | $0.00053 |
| Haiku 4.5 | $0.00002 | $0.00027 |
Grade A, and why
battlecard-library 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 9d 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.
What it actually says
Battlecard Library Skill
When to Use
- Creating/updating battlecards for new competitors.
- Packaging objection handling + differentiation guidance for field teams.
- Tracking adoption and freshness of competitive assets.
Framework
- Card Structure – overview, positioning, landmines, differentiation, trap-setting, proof, offer packaging.
- Metadata & Tagging – segment, persona, stage, product module, last updated, SME, confidence level.
- Enablement Hooks – talk tracks, snippets for sequences, asset links, CRM surfaces, content snippets.
- Review Cadence – SME assignments, refresh schedule, localization requirements.
- Analytics – usage tracking, win rate impact, prioritized backlog.
Templates
- Battlecard deck/Notion template with modular sections.
- Objection handling table (objection → talk track → asset → confidence).
- Update log spreadsheet capturing date, owner, change summary.
Tips
- Embed battlecards directly into CRM/workspace surfaces where reps already work.
- Flag trap-setting and landmines clearly to avoid disclosure mistakes.
- Pair with
build-battlecard-suitecommand to automate population.
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.
- 9d ago First seen · 31 lines · 17 tokens per session scan A 639d39980328
battlecard-library is a skill published in the GitHub repository gtmagents/gtm-agents (399 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 17 tokens to every session and 266 once invoked, about $0.0001 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 2026-09-03.
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…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
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…