Notre avis
Effectue des recherches sur n'importe quel sujet en interrogeant directement l'API Exa via curl, produisant des rapports structurés en markdown sans consommer de tokens Claude Code.
Points forts
- Zéro consommation de tokens Claude
- Accès direct à l'API avec types de recherche flexibles (web, code, entreprise)
- Sauvegarde des résultats dans des fichiers markdown locaux pour référence future
- Produit des rapports finaux structurés avec résumé exécutif et sources
Limites
- Nécessite une clé API Exa et une configuration initiale
- Les résultats dépendent de la couverture et de la qualité d'Exa
- Pas de gestion d'erreur ou de réessai intégrée pour les échecs API
Quand vous avez besoin d'une recherche approfondie sur un sujet sans épuiser les tokens Claude Code, en particulier pour des requêtes complexes ou multi-sources.
Pour des recherches simples que Claude peut gérer directement avec un coût minimal en tokens, ou quand vous avez besoin de données en temps réel qu'Exa n'a peut-être pas indexées.
Analyse de sécurité
PrudenceThe skill employs Bash and curl to call an external API, loading an API key from a decrypted secret. While the intended workflow is safe, the dynamic construction of a curl command with user input and the use of powerful system tools introduces moderate risk. Proper input sanitization is implied but not explicitly enforced.
- •Uses Bash to run curl with user-supplied query in JSON string; potential for shell injection if topic is not properly escaped.
- •Decrypts an API key from an encrypted file using sops, necessitating access to sensitive credentials.
Exemples
/freesearch AI coding tools with persistent memoryFree research on latest developments in quantum computingResearch the best practices for API rate limiting without spending tokensname: freesearch description: TRULY FREE research via Exa API - zero Claude tokens. Uses Exa directly, no Gemini CLI wrapper. homepage: https://github.com/Khamel83/oneshot allowed-tools: Read, Write, Edit, Bash metadata: {"oneshot":{"emoji":"🆓","requires":{"bins":["curl"]}}}
/freesearch - TRULY FREE Research
Uses 0 Claude Code tokens. Calls Exa API directly via curl.
When To Use
User says:
/freesearch [topic]- Slash command- "Free research on [topic]"
- "Research without burning tokens"
How It Works
Direct API calls via curl:
- Ask 2-3 clarifying questions (goal, depth, audience)
- Create
docs/research/{date}_{topic}_in_progress.md - Search Exa API:
- web search for overview
- code search for technical details
- company/person search if relevant
- Update in-progress file with raw results
- Create
docs/research/{date}_{topic}_final.mdwith:- Executive summary
- Key findings
- Sources with links
- Related topics
- Return file path to Claude for reading
Exa API Configuration
The EXA_API_KEY is loaded from encrypted secrets:
# Decrypt and load key (done via skill wrapper)
EXA_KEY=$(sops --decrypt --output-type json ~/github/oneshot/secrets/research_keys.json.encrypted | grep -o '"EXA_API_KEY": "[^"]*"' | cut -d'"' -f4)
API Endpoint: https://api.exa.ai/search
Research Prompt Template
curl -s -X POST 'https://api.exa.ai/search' \
-H "x-api-key: $EXA_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"query": "[TOPIC]",
"type": "auto",
"numResults": 10,
"contents": {
"text": {
"maxCharacters": 20000
}
}
}'
Output Locations
Project research files:
docs/research/{YYYY-MM-DD}_{topic_slug}_in_progress.md
docs/research/{YYYY-MM-DD}_{topic_slug}_final.md
Historical research:
research/{topic_slug}/research.md
Quick Wins to Implement
Based on competitor research, these features should be added to ONE_SHOT:
/browsecommand - Visual skill discovery with fuzzy searchbd testframework - Skill testing framework- Diff preview - Show changes before applying
- Skill analytics - Track most-used skills
Example Usage
User says: /freesearch AI coding tools with persistent memory
You do:
-
Ask clarifying questions:
- "What's your goal?"
- "How deep should I go?"
-
Create in-progress file with initial query
-
Search Exa API:
web_search_exa: "AI coding tools persistent memory cross-session"get_code_context_exa: "AI coding task orchestration memory"
-
Update in-progress file with findings
-
Create final report with executive summary
-
Return:
Key findings: - MCP Task Orchestrator, Cipher, Pieces AI Memory, Cursor Rules - All use RAG + vector stores for persistent context 📄 Full research: docs/research/2025-01-31_ai_persistent_memory_final.md
File Format Template
In-Progress Template
# Research: {Topic}
**Started:** {timestamp}
**Status:** In Progress
## Search Queries Used
- {query1}
- {query2}
## Raw Results
### Source 1
- **URL:** {url}
- **Title:** {title}
- **Snippet:** {content}
### Source 2
- **URL:** {url}
- **Title:** {title}
- **Snippet:** {content}
## Initial Notes
{ongoing analysis}
Final Template
# Research: {Topic}
**Completed:** {timestamp}
**Duration:** {duration}
## Executive Summary
{2-3 sentence overview}
## Key Findings
1. {finding with citation}
2. {finding with citation}
## Sources
1. [{Title}]({url}) - {description}
2. [{Title}]({url}) - {description}
## Related Topics
- {topic for further research}
## Full Details
{detailed analysis}
---
📄 **In-progress research:** docs/research/{date}_{topic}_in_progress.md
Why This Exists
The deep-research skill wraps Gemini CLI in a Claude sub-agent, which still burns tokens. This skill calls Exa API directly via curl:
- ✅ 0 Claude Code tokens for research
- ✅ Only main conversation tokens (clarifying questions, summary)
- ✅ Same quality research (Exa's neural search)
- ✅ Saves to project
docs/research/(tracked in git)
Tips
- Research takes 10-30 seconds (Exa is fast)
- Always save to
docs/research/NOT~/github/oneshot/research/ - Include user's goal in the prompt for better results
- Link in-progress file in final report for drill-down
Keywords
free research, exa api, zero tokens, web search, research save
Ingénierie de Prompts
Data & IA
Bonnes pratiques et templates de prompt engineering pour maximiser les résultats IA.
Visualisation de Données
Data & IA
Génère des visualisations de données et graphiques adaptés à vos données.
Architecture RAG
Data & IA
Guide de configuration d'architectures RAG (Retrieval-Augmented Generation).