Use this read-only tool before paid ATLAS evidence evaluation to determine whether a user-written issuer thesis is monitorable. It scores issuer specificity, thesis clarity, evidence alignment, watch-condition quality, falsifiability, weakening criteria, materiality, provenance requirements, non-...
Part of the DeltaSignal ATLAS-7 server.
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AI agents invoke deltasignal_thesis_readiness to trigger processes or run actions in DeltaSignal ATLAS-7. Execute operations can have side effects beyond the immediate call -- triggering builds, sending notifications, or starting workflows. Rate limits and argument validation are essential to prevent runaway execution.
deltasignal_thesis_readiness can trigger processes with real-world consequences. An uncontrolled agent might start dozens of builds, send mass notifications, or kick off expensive compute jobs. PolicyLayer enforces rate limits and validates arguments to keep execution within safe bounds.
Execute tools trigger processes. Rate-limit and validate arguments to prevent unintended side effects.
{
"version": "1",
"default": "deny",
"tools": {
"deltasignal_thesis_readiness": {
"limits": [
{
"counter": "deltasignal_thesis_readiness_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}See the full DeltaSignal ATLAS-7 policy for all 33 tools.
These attack patterns abuse exactly the kind of access deltasignal_thesis_readiness gives an agent. Each links to the full case and the policy that stops it:
Other execute tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.
Use this read-only tool before paid ATLAS evidence evaluation to determine whether a user-written issuer thesis is monitorable. It scores issuer specificity, thesis clarity, evidence alignment, watch-condition quality, falsifiability, weakening criteria, materiality, provenance requirements, non-execution boundary, and monitoring readiness. Parameters: ticker and thesis_text are required; watch_conditions, evidence_surfaces, cadence, lookback_days, output_mode, and provenance_required are optional. Behavior: read-only and idempotent; it performs deterministic local validation only, has no destructive side effects, does not call DeltaSignal evidence routes, does not execute wallets or x402 settlement, and never returns buy, sell, hold, target-price, allocation, or order instructions. Use it as the free or low-cost thesis-structuring layer; use paid thesis baseline or evaluation only after readiness is monitor_ready or needs_cleanup.. It is categorised as a Execute tool in the DeltaSignal ATLAS-7 MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the DeltaSignal ATLAS-7 MCP server in PolicyLayer and add a rule for deltasignal_thesis_readiness: 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 DeltaSignal ATLAS-7. Nothing to install.
deltasignal_thesis_readiness is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the deltasignal_thesis_readiness 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 deltasignal_thesis_readiness. 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.
deltasignal_thesis_readiness is provided by the DeltaSignal ATLAS-7 MCP server (https://api.aitrailblazer.net/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 33 DeltaSignal ATLAS-7 tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
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