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 gethouston/houston --skill enriquecer-leads-con-apollogit clone --depth 1 https://github.com/gethouston/houstonWrote 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/gethouston/houston/enriquecer-leads-con-apollo)<a href="https://agentmods.dev/skills/gethouston/houston/enriquecer-leads-con-apollo"><img src="https://agentmods.dev/badge/skills/gethouston/houston/enriquecer-leads-con-apollo/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/gethouston/houston/enriquecer-leads-con-apollo"><img src="https://agentmods.dev/badge/skills/gethouston/houston/enriquecer-leads-con-apollo.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 | $0.00110 | $0.02164 |
| Opus 5 | $0.00055 | $0.01082 |
| Sonnet 5 | $0.00022 | $0.00433 |
| Haiku 4.5 | $0.00011 | $0.00216 |
Grade A, and why
enriquecer-leads-con-apollo 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.
How it starts
The opening of the file, as written. The whole thing — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Enriquecimiento con Apollo
Tomo una lista de leads en una tabla de Airtable y busco emails verificados para la mayor cantidad posible usando el endpoint de bulk match de Apollo. Actualizo las filas de Airtable directamente con email, empresa, cargo y ubicación, y creo contactos en Apollo bajo una etiqueta con nombre para que los leads lleguen a tus flujos de trabajo del CRM de Apollo. La tasa de coincidencia depende mucho de la audiencia, espera entre 50% y 70% en audiencias de fundadores/operadores en Estados Unidos, y menos en audiencias de consumo o fuera de Estados Unidos.
Cuándo usarme
- "Enriquece estos leads con Apollo: ".
- "Busca emails para las filas de esta tabla".
- Fase 3 de cualquiera de los dos pipelines de LinkedIn (invocada por el orquestador).
- Tienes una tabla de Airtable con
Profile URLs cargados y quieres agregarles emails.
Cuándo NO usarme
- Los leads todavía no están en Airtable, cárgalos primero con
airtable-lead-loader. - Solo quieres leer datos de Apollo, no modificar Airtable, esta habilidad escribe de vuelta en Airtable como parte de su contrato; si solo necesitas una búsqueda puntual en Apollo, hazla manualmente.
Conexiones que necesito
- Airtable (base de datos), obligatoria. Leo las filas y luego escribo de vuelta los campos de enriquecimiento.
- Apollo (enriquecimiento), obligatoria. Uso el endpoint
apollo_people_bulk_matchy el endpointapollo_contacts_createa través de Composio.
Si falta cualquiera de las dos, me detengo y te pido que la conectes.
Información que necesito
- El ID de la base de Airtable + el ID de la tabla, obligatorio. Si se invoca desde un orquestador, ambos se pasan directamente. Si se invoca de forma independiente, listo las bases y tablas y pregunto cuál si hay alguna ambigüedad.
- Una etiqueta de contacto de Apollo, opcional. Por defecto es
LinkedIn {sourceType} - {sourceAuthor} Post, derivada de los camposSource TypeySource Authorde la tabla (toda fila de una tabla dada tiene el mismo origen). Puedes indicar otra por llamada.
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 · 112 lines · 110 tokens per session scan A d52acabebd1d
enriquecer-leads-con-apollo is a skill published in the GitHub repository gethouston/houston (113 stars, last pushed today), licensed MIT. It adds 110 tokens to every session and 2,164 once invoked, about $0.0006 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.
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