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-prospectgit 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-prospect)<a href="https://agentmods.dev/skills/anysiteio/agent-skills/anysite-crm-prospect"><img src="https://agentmods.dev/badge/skills/anysiteio/agent-skills/anysite-crm-prospect/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-prospect"><img src="https://agentmods.dev/badge/skills/anysiteio/agent-skills/anysite-crm-prospect.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 | $0.00106 | $0.01362 |
| Opus 5 | $0.00053 | $0.00681 |
| Sonnet 5 | $0.00021 | $0.00272 |
| Haiku 4.5 | $0.00011 | $0.00136 |
Grade A, and why
anysite-crm-prospect 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 — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CRM Prospect
Search → resolve → dedup → create. Order matters: companies before contacts, dedup before create, dry-run before both.
Prerequisites
Active CRM connection + profile (allow_create: true agreed in profile — if not, stop and
ask). Read Writing rules in anysite-crm-setup.
Flow
1. Define the search
Get concrete criteria from the user (persona titles, industry, geography, size, stage). Estimate volume and confirm before running anything large.
Companies:
execute linkedin/search/search_sql_companies— main path:keywords/industry_nameDSL,employee_count_min/max,country_hq, up to 1000/call, 1cr-class.execute crunchbase/db/db_search— when stage/funding filters matter (last_funding_type,last_funding_date_after,investors).execute crunchbase/search— live, addshiring: true,it_spend_*,valuation_*filters (20cr/50 — use for precision, not volume).
People at those companies:
- Bulk (default):
execute linkedin/search/search_sql_users— filter bycurrent_company_id/current_company_domain(straight from the company results),seniority_min/function(derived — better recall than title text), country. Craft + coverage caveats:anysite-people-sourcingskill. >1000 matches → walkbucket_total/bucket_index, not repeated calls. - Point lookups / disambiguation:
execute linkedin/search/search_users {job_title, current_company: [urn] | company_keywords, location, count}— never barekeywords. - Live-verify the outreach shortlist via
linkedin/userbefore pushing — the DB is fresh but not realtime.
2. Emails (cheap-first cascade)
execute linkedin/user/user_email— batches of ≤10 profiles. Warn the user upfront: yield is low, a large share of leads will come back email-less.- Remainder →
user_find_email_by_url {url: <vanity profile URL>}— high yield, 50cr each: estimate the cost (50cr × remainder) and confirm before running on large lists. Vanity URLs only (/in/name/, not/in/ACoA...). Itsvalid_email/email_statusfields are the deliverability gate: only validated work addresses go into the push; the rest stay "found, unverified". - Still nothing → keep the lead in the report, but know the server requires an email
to CREATE a contact — email-less leads can only update existing records (matched by
linkedin_url). Report them as "found, pending email"; never silently drop them.
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 · 105 lines · 106 tokens per session scan A 6fba80cf4f85
anysite-crm-prospect is a skill published in the GitHub repository anysiteio/agent-skills (19 stars, last pushed 27d ago), licensed MIT. It adds 106 tokens to every session and 1,362 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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