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 anysiteio/agent-skills --skill anysite-crm-competitor-intelgit clone --depth 1 https://github.com/anysiteio/agent-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/anysiteio/agent-skills/anysite-crm-competitor-intel)<a href="https://agentmods.dev/skills/anysiteio/agent-skills/anysite-crm-competitor-intel"><img src="https://agentmods.dev/badge/skills/anysiteio/agent-skills/anysite-crm-competitor-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/anysiteio/agent-skills/anysite-crm-competitor-intel"><img src="https://agentmods.dev/badge/skills/anysiteio/agent-skills/anysite-crm-competitor-intel.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00108 | $0.01005 |
| Opus 5 | $0.00054 | $0.00502 |
| Sonnet 5 | $0.00022 | $0.00201 |
| Haiku 4.5 | $0.00011 | $0.00101 |
Grade A, and why
anysite-crm-competitor-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.
How it starts
The opening of the file, as written. The whole thing — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CRM Competitor Intel
Competitor-switch signals are the highest-intent plays in signal-based selling. This skill builds the target list and the ammunition: who uses the competitor, and what their users complain about.
Prerequisites
Active CRM connection for the cross-reference/tagging part (Writing rules from
anysite-crm-setup apply to tagging). The research part works without one.
Flow
1. Who uses the competitor (technographics)
Only works for competitors whose product is detectable on websites (martech, analytics, chat widgets, ecommerce...):
execute wappalyzer/technologies {technology: "<competitor slug>"}
→ website_count (market size), top_websites[] (sample of users, with traffic/tech-spend),
alternatives[] (the category landscape), top_countries
Honest limitation: top_websites is a sample, not an exhaustive list. Frame it as
"examples + market sizing", supplement with linkedin/search/search_sql_companies
searching the competitor name in specialities/description, and with
producthunt/products/products_alternatives for the category graph.
Not website-detectable (e.g. a database vendor)? Skip to reviews and search: job posts
mentioning the tool (linkedin/search/search_jobs {keywords: "<tool>"} — companies whose
vacancies require competitor experience are its customers), reddit/community mentions.
2. What their users complain about (review mining)
execute capterra/products/products_search {query: "<competitor>", count: 5} → seo_id
execute capterra/products/products_reviews {product: "<seo_id>", count: 50}
The product param wants the seo_id field (not id). Reviews include switched_from[],
switching_reason and chosen_reason — direct competitor-switch evidence, mine these
first. Same pattern via trustradius and getapp products_reviews (g2 exposes search
only). Filter low-rating reviews with query_cache (free), then extract with the LLM:
recurring pains, switching triggers, praised alternatives, verbatim quotes worth reusing.
Keep 3–7 pains with quote + source URL each — this is the personalization ammunition.
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 · 84 lines · 108 tokens per session scan A 07826cf45828
anysite-crm-competitor-intel is a skill published in the GitHub repository anysiteio/agent-skills (19 stars, last pushed 27d ago), licensed MIT. It adds 108 tokens to every session and 1,005 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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