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 danielgap/openclaw-planitor --skill pipeline-market-analysisgit clone --depth 1 https://github.com/danielgap/openclaw-planitorWrote 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/danielgap/openclaw-planitor/pipeline-market-analysis)<a href="https://agentmods.dev/skills/danielgap/openclaw-planitor/pipeline-market-analysis"><img src="https://agentmods.dev/badge/skills/danielgap/openclaw-planitor/pipeline-market-analysis/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/danielgap/openclaw-planitor/pipeline-market-analysis"><img src="https://agentmods.dev/badge/skills/danielgap/openclaw-planitor/pipeline-market-analysis.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 | $0.00032 | $0.00758 |
| Opus 5 | $0.00016 | $0.00379 |
| Sonnet 5 | $0.00006 | $0.00152 |
| Haiku 4.5 | $0.00003 | $0.00076 |
Grade A, and why
pipeline-market-analysis scanned grade A with 1 finding 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 10d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl → Jina AI → SearXNG → Lightpanda → Scrapling stealthy How it starts
The opening of the file, as written. The whole thing — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pipeline Market Analysis — MarketAgent
Input
| Archivo | Descripción |
|---|---|
GROUND-TRUTH.json |
Supuestos validados de la Fase 2 |
Output
projects/{proyecto}/v{n}/MARKET-ANALYSIS.json
{
"tam": 0, "sam": 0, "som": 0,
"competidores_directos": [],
"competidores_indirectos": [],
"tendencias": [],
"estacionalidad": {},
"oportunidades": [],
"riesgos_mercado": [],
"subvenciones": []
}
Cada competidor: { nombre, tipo, precio_real, indoor/outdoor, url_verificada, fecha_consulta }
Frameworks
- Market Analysis — TAM/SAM/SOM, Porter's Five Forces
- Business Model Canvas — Customer Segments, Channels
- Lean Canvas — Existing Alternatives
Prompt Guía
Lee projects/{proyecto}/v{n}/GROUND-TRUTH.json y realiza un análisis de mercado completo.
INVESTIGACIÓN:
1. Competencia directa (3-5 competidores con URL y precio verificado)
2. Competencia indirecta (si hay eventos grupales: ludotecas, restaurantes, etc.)
3. TAM/SAM/SOM con cálculo bottom-up
4. Tendencias del mercado
5. Estacionalidad (tabla mensual si aplica)
6. Subvenciones disponibles
7. Oportunidades y riesgos
HERRAMIENTAS DISPONIBLES PARA INVESTIGACIÓN:
- **SearXNG**: `python3 ~/.openclaw/workspace/skills/searxng-search/searxng-search.py "[tipo negocio] [ciudad]"`
- **Tavily**: Búsqueda web primaria (via web_search tool)
- **Google Reviews**: `xvfb-run python3 ~/.openclaw/workspace/agents/extractor/skills/google-reviews-extract/google_reviews_camoufox.py "Nombre" "Ciudad"`
- **registro-empresas-es**: Datos societarios de competidores (CIF, cuentas, admin)
- **trends-checker**: Demanda consciente con Google Trends
- **reddit-readonly**: `node ~/.openclaw/workspace/skills/reddit-readonly/reddit-readonly.mjs "[sector] [ciudad]"`
- **twitter-extract**: Actividad redes sociales de competidores
- **subvencion-watcher**: Búsqueda de subvenciones
- **company-research**: Pipeline completo de investigación (delegar a Scout si competidor complejo)
FALLBACK CHAIN (para cualquier URL):
curl → Jina AI → SearXNG → Lightpanda → Scrapling stealthy
Para cada competidor: nombre, tipo, precio real, URL verificada, fecha consulta.
Si no puedes verificar un precio, márcalo como "no publicado". No inventes competidores.
Guarda como MARKET-ANALYSIS.json en projects/{proyecto}/v{n}/
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.
- 10d ago First seen · 83 lines · 32 tokens per session scan A 5ff3f58b67d7
pipeline-market-analysis is a skill published in the GitHub repository danielgap/openclaw-planitor (5 stars, last pushed 4mo ago), licensed MIT. It adds 32 tokens to every session and 758 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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