OpenAgentSkill
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agiprolabs

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coingecko-api

Broad crypto market data from CoinGecko covering 13,000+ tokens. Global market stats, historical price data going back years, exchange volumes, trending tokens, and category filters. Best for macro analysis and long-term historical data.

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Prix non confirmé★ 345 Stars GitHubRegistre mis à jour · 5 sept. 2026agent-skill

Vue d’ensemble

Broad crypto market data from CoinGecko covering 13,000+ tokens. Global market stats, historical price data going back years, exchange volumes, trending tokens, and category filters. Best for macro analysis and long-term historical data.

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Documentation source, pas des instructions pour ce site. Vérifiez les permissions avant d’exécuter des commandes.

CoinGecko API Skill

Query the CoinGecko API for comprehensive crypto market data — prices, historical charts, exchange volumes, trending tokens, global stats, and category breakdowns. The free tier requires no API key and supports 30 calls/min.

When to Use This Skill

  • Macro analysis: Global market cap, BTC dominance, total volume trends
  • Historical data: Daily/hourly OHLCV going back years (not minutes-level)
  • Cross-exchange comparisons: Exchange volume rankings and trust scores
  • Trending/discovery: What tokens are trending on CoinGecko in the last 24h
  • Category analysis: Compare DeFi vs L1 vs meme coin market caps
  • Token research: Full metadata including links, description, community stats

Use Birdeye or DexScreener instead for real-time Solana DEX data, new token launches, or sub-daily granularity on Solana tokens.

Quick Start

Get Current Prices
import httpx

# No API key needed for free tier
resp = httpx.get(
    "https://api.coingecko.com/api/v3/simple/price",
    params={"ids": "solana,bitcoin,ethereum", "vs_currencies": "usd",
            "include_24hr_change": "true"},
)
data = resp.json()
for coin, info in data.items():
    print(f"{coin}: ${info['usd']:.2f} ({info['usd_24h_change']:+.1f}%)")
Get Top Coins by Market Cap
import httpx

resp = httpx.get(
    "https://api.coingecko.com/api/v3/coins/markets",
    params={"vs_currency": "usd", "order": "market_cap_desc",
            "per_page": 10, "page": 1, "sparkline": "false"},
)
for coin in resp.json():
    print(f"{coin['symbol'].upper():>6}  ${coin['current_price']:>10,.2f}  "
          f"MCap: ${coin['market_cap']/1e9:.1f}B  "
          f"24h: {coin['price_change_percentage_24h']:+.1f}%")
Get Historical Price Data
import httpx
import pandas as pd

resp = httpx.get(
    "https://api.coingecko.com/api/v3/coins/solana/market_chart",
    params={"vs_currency": "usd", "days": "90", "interval": "daily"},
)
data = resp.json()
df = pd.DataFrame(data["prices"], columns=["timestamp", "price"])
df["date"] = pd.to_datetime(df["timestamp"], unit="ms")
df = df.set_index("date").drop(columns=["timestamp"])
print(df.describe())
Get OHLC Candle Data
import httpx

resp = httpx.get(
    "https://api.coingecko.com/api/v3/coins/solana/ohlc",
    params={"vs_currency": "usd", "days": "30"},
)
# Returns [[timestamp, open, high, low, close], ...]
candles = resp.json()
for c in candles[-5:]:
    print(f"  O={c[1]:.2f}  H={c[2]:.2f}  L={c[3]:.2f}  C={c[4]:.2f}")
Global Market Stats
import httpx

resp = httpx.get("https://api.coingecko.com/api/v3/global")
g = resp.json()["data"]
print(f"Total Market Cap:  ${g['total_market_cap']['usd']/1e12:.2f}T")
print(f"24h Volume:        ${g['total_volume']['usd']/1e9:.0f}B")
print(f"BTC Dominance:     {g['market_cap_percentage']['btc']:.1f}%")
print(f"Active Coins:      {g['active_cryptocurrencies']:,}")

import httpx

resp = httpx.get("https://api.coingecko.com/api/v3/search/trending")
for item in resp.json()["coins"]:
    coin = item["item"]
    print(f"#{coin['market_cap_rank'] or '?':>4}  {coin['name']} ({coin['symbol']})")

Authentication

The free tier requires no API key (30 calls/min). For higher limits, get a Pro key from https://www.coingecko.com/en/api/pricing and set:

export COINGECKO_API_KEY="CG-xxxxxxxxxxxxxxxxxxxx"

Pro requests use a different base URL and header:

import os, httpx

API_KEY = os.getenv("COINGECKO_API_KEY", "")
if API_KEY:
    BASE_URL = "https://pro-api.coingecko.com/api/v3"
    HEADERS = {"x-cg-pro-api-key": API_KEY}
else:
    BASE_URL = "https://api.coingecko.com/api/v3"
    HEADERS = {}

Rate Limiting

Free tier: 30 requests/min. Implement backoff on 429 responses:

import time, httpx

def cg_get(url: str, params: dict, max_retries: int = 3) -> dict:
    """GET with retry on rate limit."""
    for attempt in range(max_retries):
        resp = httpx.get(url, params=params, headers=HEADERS, timeout=15.0)
        if resp.status_code == 429:
            wait = 2 ** attempt * 10
            print(f"Rate limited, waiting {wait}s...")
            time.sleep(wait)
            continue
        resp.raise_for_status()
        return resp.json()
    raise RuntimeError("Max retries exceeded")

Finding CoinGecko Token IDs

CoinGecko uses slug-style IDs (e.g., solana, bitcoin, usd-coin). To find an ID from a contract address or name, see references/id_mapping.md.

Quick lookup by contract address (useful for Solana tokens):

import httpx

# Look up by Solana contract address
contract = "So11111111111111111111111111111111111111112"
resp = httpx.get(
    "https://api.coingecko.com/api/v3/coins/solana/contract/"
    + contract
)
coin = resp.json()
print(f"ID: {coin['id']}, Name: {coin['name']}")

Key Limitations

  • No real-time data: Prices update every 1-2 minutes on free tier
  • Limited Solana coverage: Many newer Solana tokens are not listed
  • OHLC granularity: Only 1/7/14/30/90/180/365 day windows, candle size depends on the window (see references/endpoints.md)
  • Historical gaps: Some tokens have missing data for early periods
  • Free tier throttling: 30 req/min means batch operations need careful pacing

See references/data_quality.md for detailed notes on data gaps and tier differences.

Files

References
  • references/endpoints.md — Complete endpoint reference with parameters, response schemas, and rate limits
  • references/id_mapping.md — How to find CoinGecko IDs for tokens, contract address mapping, search tips
  • references/data_quality.md — Data quality notes, historical gaps, free vs pro tier differences
Scripts
  • scripts/fetch_market_data.py — Fetch top coins, trending tokens, and global stats (supports --demo mode)
  • scripts/historical_analysis.py — Fetch historical OHLCV data and compute returns, volatility, drawdown (supports --demo mode)
Voir la source ↗
Métadonnées du fichier
name: coingecko-api
description: >
  Broad crypto market data from CoinGecko covering 13,000+ tokens. Global market
  stats, historical price data going back years, exchange volumes, trending tokens,
  and category filters. Best for macro analysis and long-term historical data.
dependencies:
  - httpx
  - pandas
  - numpy
tags:
  - api
  - market-data
  - crypto
  - historical
  - macro
Voir le texte original
---
name: coingecko-api
description: >
  Broad crypto market data from CoinGecko covering 13,000+ tokens. Global market
  stats, historical price data going back years, exchange volumes, trending tokens,
  and category filters. Best for macro analysis and long-term historical data.
dependencies:
  - httpx
  - pandas
  - numpy
tags:
  - api
  - market-data
  - crypto
  - historical
  - macro
---

# CoinGecko API Skill

Query the CoinGecko API for comprehensive crypto market data — prices, historical
charts, exchange volumes, trending tokens, global stats, and category breakdowns.
The free tier requires no API key and supports 30 calls/min.

## When to Use This Skill

- **Macro analysis**: Global market cap, BTC dominance, total volume trends
- **Historical data**: Daily/hourly OHLCV going back years (not minutes-level)
- **Cross-exchange comparisons**: Exchange volume rankings and trust scores
- **Trending/discovery**: What tokens are trending on CoinGecko in the last 24h
- **Category analysis**: Compare DeFi vs L1 vs meme coin market caps
- **Token research**: Full metadata including links, description, community stats

Use **Birdeye** or **DexScreener** instead for real-time Solana DEX data, new token
launches, or sub-daily granularity on Solana tokens.

## Quick Start

### Get Current Prices

```python
import httpx

# No API key needed for free tier
resp = httpx.get(
    "https://api.coingecko.com/api/v3/simple/price",
    params={"ids": "solana,bitcoin,ethereum", "vs_currencies": "usd",
            "include_24hr_change": "true"},
)
data = resp.json()
for coin, info in data.items():
    print(f"{coin}: ${info['usd']:.2f} ({info['usd_24h_change']:+.1f}%)")
```

### Get Top Coins by Market Cap

```python
import httpx

resp = httpx.get(
    "https://api.coingecko.com/api/v3/coins/markets",
    params={"vs_currency": "usd", "order": "market_cap_desc",
            "per_page": 10, "page": 1, "sparkline": "false"},
)
for coin in resp.json():
    print(f"{coin['symbol'].upper():>6}  ${coin['current_price']:>10,.2f}  "
          f"MCap: ${coin['market_cap']/1e9:.1f}B  "
          f"24h: {coin['price_change_percentage_24h']:+.1f}%")
```

### Get Historical Price Data

```python
import httpx
import pandas as pd

resp = httpx.get(
    "https://api.coingecko.com/api/v3/coins/solana/market_chart",
    params={"vs_currency": "usd", "days": "90", "interval": "daily"},
)
data = resp.json()
df = pd.DataFrame(data["prices"], columns=["timestamp", "price"])
df["date"] = pd.to_datetime(df["timestamp"], unit="ms")
df = df.set_index("date").drop(columns=["timestamp"])
print(df.describe())
```

### Get OHLC Candle Data

```python
import httpx

resp = httpx.get(
    "https://api.coingecko.com/api/v3/coins/solana/ohlc",
    params={"vs_currency": "usd", "days": "30"},
)
# Returns [[timestamp, open, high, low, close], ...]
candles = resp.json()
for c in candles[-5:]:
    print(f"  O={c[1]:.2f}  H={c[2]:.2f}  L={c[3]:.2f}  C={c[4]:.2f}")
```

### Global Market Stats

```python
import httpx

resp = httpx.get("https://api.coingecko.com/api/v3/global")
g = resp.json()["data"]
print(f"Total Market Cap:  ${g['total_market_cap']['usd']/1e12:.2f}T")
print(f"24h Volume:        ${g['total_volume']['usd']/1e9:.0f}B")
print(f"BTC Dominance:     {g['market_cap_percentage']['btc']:.1f}%")
print(f"Active Coins:      {g['active_cryptocurrencies']:,}")
```

### Trending Coins

```python
import httpx

resp = httpx.get("https://api.coingecko.com/api/v3/search/trending")
for item in resp.json()["coins"]:
    coin = item["item"]
    print(f"#{coin['market_cap_rank'] or '?':>4}  {coin['name']} ({coin['symbol']})")
```

## Authentication

The free tier requires no API key (30 calls/min). For higher limits, get a Pro
key from https://www.coingecko.com/en/api/pricing and set:

```bash
export COINGECKO_API_KEY="CG-xxxxxxxxxxxxxxxxxxxx"
```

Pro requests use a different base URL and header:

```python
import os, httpx

API_KEY = os.getenv("COINGECKO_API_KEY", "")
if API_KEY:
    BASE_URL = "https://pro-api.coingecko.com/api/v3"
    HEADERS = {"x-cg-pro-api-key": API_KEY}
else:
    BASE_URL = "https://api.coingecko.com/api/v3"
    HEADERS = {}
```

## Rate Limiting

Free tier: 30 requests/min. Implement backoff on 429 responses:

```python
import time, httpx

def cg_get(url: str, params: dict, max_retries: int = 3) -> dict:
    """GET with retry on rate limit."""
    for attempt in range(max_retries):
        resp = httpx.get(url, params=params, headers=HEADERS, timeout=15.0)
        if resp.status_code == 429:
            wait = 2 ** attempt * 10
            print(f"Rate limited, waiting {wait}s...")
            time.sleep(wait)
            continue
        resp.raise_for_status()
        return resp.json()
    raise RuntimeError("Max retries exceeded")
```

## Finding CoinGecko Token IDs

CoinGecko uses slug-style IDs (e.g., `solana`, `bitcoin`, `usd-coin`). To find
an ID from a contract address or name, see `references/id_mapping.md`.

Quick lookup by contract address (useful for Solana tokens):

```python
import httpx

# Look up by Solana contract address
contract = "So11111111111111111111111111111111111111112"
resp = httpx.get(
    "https://api.coingecko.com/api/v3/coins/solana/contract/"
    + contract
)
coin = resp.json()
print(f"ID: {coin['id']}, Name: {coin['name']}")
```

## Key Limitations

- **No real-time data**: Prices update every 1-2 minutes on free tier
- **Limited Solana coverage**: Many newer Solana tokens are not listed
- **OHLC granularity**: Only 1/7/14/30/90/180/365 day windows, candle size
  depends on the window (see `references/endpoints.md`)
- **Historical gaps**: Some tokens have missing data for early periods
- **Free tier throttling**: 30 req/min means batch operations need careful pacing

See `references/data_quality.md` for detailed notes on data gaps and tier differences.

## Files

### References
- `references/endpoints.md` — Complete endpoint reference with parameters, response schemas, and rate limits
- `references/id_mapping.md` — How to find CoinGecko IDs for tokens, contract address mapping, search tips
- `references/data_quality.md` — Data quality notes, historical gaps, free vs pro tier differences

### Scripts
- `scripts/fetch_market_data.py` — Fetch top coins, trending tokens, and global stats (supports `--demo` mode)
- `scripts/historical_analysis.py` — Fetch historical OHLCV data and compute returns, volatility, drawdown (supports `--demo` mode)

Examiner la source

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Licence
MIT
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Source du skill enregistrée

Un chemin vers les instructions est enregistré. Cela ne constitue pas un test, une garantie de sécurité ou de compatibilité.

Réviser avant installation: Éviter l’installation automatique

Licence: MIT

  • Dependency or permission surface needs review
  • Permission surface may require sandboxing
  • Financial research output is not financial advice; require human review before any live investment decision
  • No critical security risks found. The skill only makes HTTP requests to CoinGecko and performs local data analysis.
  • External API data is printed directly; if this output is later consumed by an LLM, standard output sanitization should be considered.
  • The SKILL.md frontmatter lists pandas and numpy as dependencies, but the Quick Start examples only use httpx. Scripts do require pandas/numpy, so this is correct overall but could be clearer.
  • Financial research output is not financial advice; require human review before any live investment decision.
  • Quality score needs review
  • Permission surface needs review: secrets or environment access, shell or command execution
  • Dependency/runtime risk: command execution surface, credential or environment access
  • Permission surface: secrets or environment access, shell or command execution
Ouvrir l’audit complet

Les outils sont des indications de métadonnées, pas une compatibilité testée. Les prompts sont des suggestions.

Commencer par une petite tâche

  1. 1Lisez la source et confirmez entrées, résultats, dépendances et permissions.
  2. 2Demandez un plan à l’agent. Approuvez la configuration et les coûts avant un test isolé.
  3. 3Vérifiez résultats et fichiers modifiés. Signalez uniquement ce qui a été exécuté et conservez la révision source.

Vérifiez les dépendances, clés API et frais externes dans la source. Un dépôt public ne rend pas tous les services gratuits.

Source et conseils d’utilisation

Répertorié

Métadonnées et examens sont indicatifs. Popularité, découverte et exécution réussie sont des faits distincts.

Dépôt source
agiprolabs/claude-trading-skills
Licence
MIT
Version
1.0.0
Dernier push GitHub
3 sept. 2026
Registre mis à jour
5 sept. 2026
Chemin des instructions
skills/coingecko-api/SKILL.md @ 981e1d736cdc

Version déclarée dans le registre ; vérifiez les versions de la source.

Qualité

69/100

Prometteur

Confiance

55/100

Do not auto-install

Audit

73/100

Revue nécessaire

Ouvrir l’audit completVoir le rapport d’évaluation
  • Dependency or permission surface needs review
  • Permission surface may require sandboxing
  • Financial research output is not financial advice; require human review before any live investment decision
  • No critical security risks found. The skill only makes HTTP requests to CoinGecko and performs local data analysis.
  • External API data is printed directly; if this output is later consumed by an LLM, standard output sanitization should be considered.
  • The SKILL.md frontmatter lists pandas and numpy as dependencies, but the Quick Start examples only use httpx. Scripts do require pandas/numpy, so this is correct overall but could be clearer.
  • Financial research output is not financial advice; require human review before any live investment decision.
  • Quality score needs review
  • Permission surface needs review: secrets or environment access, shell or command execution
  • Dependency/runtime risk: command execution surface, credential or environment access
  • Permission surface: secrets or environment access, shell or command execution
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Résultats
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    "manifest_url": "https://www.openagentskill.com/api/registry/manifest/agiprolabs-coingecko-api"
  },
  "trust": {
    "score": 63,
    "label": "Manual review",
    "version": "trust-score-v4",
    "install_policy": "block",
    "evidence": {
      "stars": "345 GitHub stars",
      "repoActivity": "345 stars, 69 forks",
      "lastPushed": "1mo since push",
      "license": "MIT",
      "repository": "https://github.com/agiprolabs/claude-trading-skills/tree/main/skills/coingecko-api",
      "install": "npx skills add agiprolabs/claude-trading-skills --skill coingecko-api",
      "installSafety": "standard package or runtime install path",
      "permissionSurface": "secrets or environment access, shell or command execution",
      "documentation": "Usable metadata, review docs",
      "agentOutcomes": "No agent outcome data yet"
    },
    "outcome_evidence": {
      "total": 0,
      "successes": 0,
      "failures": 0,
      "not_relevant": 0,
      "success_rate": null,
      "recent_success_rate": null,
      "recent_failure_rate": null,
      "install_attempts": 0,
      "install_success_rate": null,
      "risk_blocked": 0,
      "setup_required": 0,
      "avg_output_quality": null,
      "production_outcomes": 0,
      "last_outcome_at": null,
      "label": "No agent outcome data yet"
    },
    "auto_install": {
      "allowed": false,
      "sandbox_required": true,
      "reason": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
    },
    "best_for": [
      "data-analysis",
      "agent-skill"
    ],
    "known_risks": [
      "No critical security risks found. The skill only makes HTTP requests to CoinGecko and performs local data analysis.",
      "Financial research output is not financial advice; require human review before any live investment decision.",
      "Quality score needs review",
      "Permission surface needs review: secrets or environment access, shell or command execution",
      "Dependency/runtime risk: command execution surface, credential or environment access",
      "Permission surface: secrets or environment access, shell or command execution"
    ]
  },
  "agent_proven": {
    "version": "agent-proven-v1",
    "score": 0,
    "tier": "unproven",
    "label": "Needs first agent run",
    "summary": "No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.",
    "metrics": {
      "totalOutcomes": 0,
      "successfulOutcomes": 0,
      "failedOutcomes": 0,
      "installAttempts": 0,
      "installSuccessRate": null,
      "successRate": null,
      "recentSuccessRate": null,
      "recentFailureRate": null,
      "riskBlocked": 0,
      "setupRequired": 0,
      "notRelevant": 0,
      "avgOutputQuality": null,
      "avgTimeToUsefulMs": null,
      "productionOutcomes": 0,
      "humanReviewRequired": 0,
      "uniqueAgents": 0,
      "lastOutcomeAt": null
    },
    "signals": [],
    "penalties": [
      "No real agent outcome evidence yet"
    ]
  },
  "audit": {
    "score": 73,
    "risk_level": "needs_review",
    "risk_label": "Needs review",
    "warnings": [
      "Dependency or permission surface needs review",
      "Permission surface may require sandboxing",
      "Financial research output is not financial advice; require human review before any live investment decision",
      "No critical security risks found. The skill only makes HTTP requests to CoinGecko and performs local data analysis.",
      "External API data is printed directly; if this output is later consumed by an LLM, standard output sanitization should be considered.",
      "The SKILL.md frontmatter lists pandas and numpy as dependencies, but the Quick Start examples only use httpx. Scripts do require pandas/numpy, so this is correct overall but could be clearer.",
      "Financial research output is not financial advice; require human review before any live investment decision.",
      "Quality score needs review"
    ]
  },
  "safety_gate": {
    "tier": "blocked",
    "label": "Blocked for auto-install",
    "auto_install_policy": "block",
    "auto_install_allowed": false,
    "human_review_required": true,
    "blocked": true,
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
  },
  "quality": {
    "score": 69,
    "label": "Promising"
  },
  "supply": {
    "track": "Data, BI, and analytics",
    "scenario": "Finance and quant",
    "maintenance": "1mo since push",
    "risk": "Needs review"
  },
  "alternative_skills": [
    {
      "slug": "ranaroussi-yfinance",
      "name": "Yfinance",
      "url": "https://www.openagentskill.com/skills/ranaroussi-yfinance",
      "stars": 24571,
      "install_command": "",
      "trust_score": 87,
      "audit_score": 89
    }
  ],
  "do_not_use_when": [
    "teams that need a vendor-supported SLA",
    "production agents without a repository review",
    "No critical security risks found. The skill only makes HTTP requests to CoinGecko and performs local data analysis.",
    "High-risk permission hints: Shell or command execution, Secrets or environment access",
    "Dependency or permission surface needs review",
    "Permission surface may require sandboxing",
    "Financial research output is not financial advice; require human review before any live investment decision",
    "External API data is printed directly; if this output is later consumed by an LLM, standard output sanitization should be considered."
  ],
  "agent_contract": {
    "task_input": "Use coingecko-api in an agent workflow",
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first.",
    "install_policy": "block",
    "minimum_review_before_use": [
      "Trust: 63/100 Manual review",
      "Audit: 73/100 Needs review",
      "Safety: 29/100 Avoid automatic install",
      "Review repository, license, install command, and permission surface before production use."
    ],
    "expected_agent_output": {
      "selected_skill": "agiprolabs-coingecko-api (coingecko-api)",
      "install_command": "npx skills add agiprolabs/claude-trading-skills --skill coingecko-api",
      "risk_summary": "Needs review; Blocked for auto-install; Review before production",
      "verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
    }
  },
  "outcome_feedback": {
    "endpoint": "https://www.openagentskill.com/api/agent/outcome",
    "method": "POST",
    "requires_resolve_event_id": true,
    "event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
    "expected_outcomes": [
      "success",
      "failed",
      "not_relevant",
      "blocked_by_risk",
      "setup_required"
    ],
    "payload_template": {
      "event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
      "skill_slug": "agiprolabs-coingecko-api",
      "task": "Use coingecko-api in an agent workflow",
      "agent": "codex",
      "outcome": "success",
      "install_used": true,
      "risk_blocked": false,
      "setup_required": false,
      "task_success": true,
      "output_quality": 4,
      "error_type": null,
      "human_review_required": false,
      "workspace": "sandbox",
      "time_to_useful_ms": 120000,
      "notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
    }
  },
  "endpoints": {
    "web": "https://www.openagentskill.com/skills/agiprolabs-coingecko-api",
    "api": "https://www.openagentskill.com/api/agent/skills/agiprolabs-coingecko-api",
    "audit": "https://www.openagentskill.com/skills/agiprolabs-coingecko-api/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=agiprolabs-coingecko-api&task=Use%20coingecko-api%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20coingecko-api%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20coingecko-api%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/agiprolabs-coingecko-api/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/agiprolabs-coingecko-api"
  }
}

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Cette fiche a été indexée à partir de sources publiques et n’est pas marquée officielle tant qu’une revendication de mainteneur n’est pas approuvée.

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agiprolabs
Indexé par
Index communautaire OpenAgentSkill

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