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 SELAT-AI/selat-skills --skill gtm-enrichment-smartgit clone --depth 1 https://github.com/SELAT-AI/selat-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/selat-ai/selat-skills/gtm-enrichment-smart)<a href="https://agentmods.dev/skills/selat-ai/selat-skills/gtm-enrichment-smart"><img src="https://agentmods.dev/badge/skills/selat-ai/selat-skills/gtm-enrichment-smart/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/selat-ai/selat-skills/gtm-enrichment-smart"><img src="https://agentmods.dev/badge/skills/selat-ai/selat-skills/gtm-enrichment-smart.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 | $0.00143 | $0.02038 |
| Opus 5 | $0.00072 | $0.01019 |
| Sonnet 5 | $0.00029 | $0.00408 |
| Haiku 4.5 | $0.00014 | $0.00204 |
Grade A, and why
gtm-enrichment-smart 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 — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.
gtm-enrichment-smart
When To Use
Use when the user hands you a lead's email (optionally a name/domain) and wants enriched person + company intelligence: title, LinkedIn, location, email deliverability, company description, funding, AI/B2B classification, and buying signals. The skill spends proportionally to lead quality — cheap primary calls first, conditional gap-fills only when earlier results leave gaps. Steps 1-7 are MPP on Tempo payments through the SELAT Router; the final Twitter social-proof step is a via the SELAT Router x402 call to SELAT-native via the SELAT Router (Circle Gateway-batched).
Workflow
- Install:
selat skill install gtm-enrichment-smart - Run:
selat skill run gtm-enrichment-smart --email [email protected] [--domain acme.com] [--organizationId <apollo_org_id>] [--twitterHandle acmehq] - The CLI compiles each manifest step into a
selat-paycall (capped at its per-stepmaxAmount), runs them in order, and prints a per-step ✓/✗ summary.
Waterfall order (the manifest runs them sequentially; later steps are conditional and should be gated by the caller on earlier results). Prices are live router quotes, probe-verified 2026-07-10:
- Step 1 — Apollo (via Locus)
POST /apollo/people-enrichment($0.0084) — primary person + embedded company/funding. Captureorganization.idfor the job-postings step. This is also the person fallback: the old separate AI person-fallback step mapped to this same endpoint with the same params, so the two were merged into this single step. - Step 2 — Hunter (via Locus)
POST /hunter/combined-enrichment($0.02415) — combined person+company cross-reference from the email. - Step 3 — Hunter (via Locus)
POST /hunter/email-verifier($0.0084) — email deliverability (valid/risky/undeliverable). - Step 4 — Abstract Company Enrichment (via Locus)
POST /abstract-company-enrichment/lookup($0.0063) — company description, industry/SIC, and firmographics. Skip for free-email domains. - Step 5 — Apollo (via Locus)
POST /apollo/org-enrichment($0.0084) — funding/headcount gap-fill, only if step 1 returned no funding. - Step 6 — Hunter (via Locus)
POST /hunter/email-enrichment($0.01365) — person tie-breaker, only if Apollo and Hunter disagree on name/title. - Step 7 — Hunter (via Locus)
POST /hunter/company-enrichment($0.01365) — company fallback, only if major gaps remain and the company has >500 employees. - Step 8 — SELAT-native (x402 via Circle Gateway)
GET /twitter/user/info?userName=…($0.001) — follower social proof, only if a Twitter handle was found. x402 via Circle Gateway. - Optional caller-invoked signal (not a manifest step) — Apollo (via Locus)
POST /apollo/job-postingsbody{"organization_id":"${organizationId}"}($0.00525) — hiring signals. Theorganization_idcomes from the step-1 people-enrichment (or an org-search) result; only invoke it once an org id was captured.
What ships with it
3 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 · 79 lines · 143 tokens per session scan A fa53e3ddfae3
gtm-enrichment-smart is a skill published in the GitHub repository SELAT-AI/selat-skills (2 stars, last pushed today), licensed Apache-2.0. It adds 143 tokens to every session and 2,038 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.
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