Keyless social-signal intel (Surf-class lane, cohort 3rd proven spend ~14x). Pass ?topic=<query> (e.g. "ai agents") and get ONE attested JSON: HN primary (title, points, num_comments, url, created_at via Algolia) + Reddit secondary (title, score, num_comments, url, created_utc; graceful empty on ...
Part of the LION - keyless data for AI agents: CPG, enrichment, social (attested) server.
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AI agents call lion_social_signal_intel to retrieve information from LION - keyless data for AI agents: CPG, enrichment, social (attested) without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.
Even though lion_social_signal_intel only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.
Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.
{
"version": "1",
"default": "deny",
"tools": {
"lion_social_signal_intel": {}
}
}See the full LION - keyless data for AI agents: CPG, enrichment, social (attested) policy for all 20 tools.
These attack patterns abuse exactly the kind of access lion_social_signal_intel gives an agent. Each links to the full case and the policy that stops it:
Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.
Keyless social-signal intel (Surf-class lane, cohort 3rd proven spend ~14x). Pass ?topic=<query> (e.g. "ai agents") and get ONE attested JSON: HN primary (title, points, num_comments, url, created_at via Algolia) + Reddit secondary (title, score, num_comments, url, created_utc; graceful empty on 429/block). Mechanical trend_score (points+comments weighted by recency, documented formula). Ed25519-attested. Sources cited. Public post metadata only, no PII. $0.004 USDC on Base via x402. Mechanical open data; not financial/investment/legal advice. [x402 paid tool: GET /api/x402/social-signal-intel-json?src=mcp returns the 402 challenge with the canonical payTo; price 0.004 USDC on Base eip155:8453.]. It is categorised as a Read tool in the LION - keyless data for AI agents: CPG, enrichment, social (attested) MCP Server, which means it retrieves data without modifying state.
Register the LION - keyless data for AI agents: CPG, enrichment, social (attested) MCP server in PolicyLayer and add a rule for lion_social_signal_intel: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches LION - keyless data for AI agents: CPG, enrichment, social (attested). Nothing to install.
lion_social_signal_intel is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the lion_social_signal_intel rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for lion_social_signal_intel. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
lion_social_signal_intel is provided by the LION - keyless data for AI agents: CPG, enrichment, social (attested) MCP server (https://lionx402.com/api/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 20 LION - keyless data for AI agents: CPG, enrichment, social (attested) tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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