Low Risk

detect_intent_conflicts

Find intents from other team members that potentially conflict with the active intent. When to use: - Before committing, to surface overlapping team work so the user can coordinate before merging. Inputs of note: - intentId: the active intent to check against. - minScore (optional): minimum match...

Part of the Kawa Code MCP server.

detect_intent_conflicts is read-only, but an agent in a loop can still rack up calls and cost. PolicyLayer caps every call before it runs. Live in minutes.

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AI agents call detect_intent_conflicts to retrieve information from Kawa Code MCP 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 detect_intent_conflicts 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.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "detect_intent_conflicts": {}
  }
}

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These attack patterns abuse exactly the kind of access detect_intent_conflicts gives an agent. Each links to the full case and the policy that stops it:

Browse the full MCP Attack Database →

Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so detect_intent_conflicts only ever does what you allow.

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Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.

What does the detect_intent_conflicts tool do? +

Find intents from other team members that potentially conflict with the active intent. When to use: - Before committing, to surface overlapping team work so the user can coordinate before merging. Inputs of note: - intentId: the active intent to check against. - minScore (optional): minimum match score to include in results. Returns scored conflict candidates with: - score: how strongly the candidate matches (higher = more likely conflict). - overlappingFiles: files affected by both intents. - decisions: decisions attached to the conflicting intent. - author: who is working on the conflicting intent. The list is informational — review candidates and their decisions to decide whether coordination is needed.. It is categorised as a Read tool in the Kawa Code MCP MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on detect_intent_conflicts? +

Register the Kawa Code MCP server in PolicyLayer and add a rule for detect_intent_conflicts: 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 Kawa Code MCP. Nothing to install.

What risk level is detect_intent_conflicts? +

detect_intent_conflicts is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit detect_intent_conflicts? +

Yes. Add a rate_limit block to the detect_intent_conflicts 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.

How do I block detect_intent_conflicts completely? +

Set action: deny in the PolicyLayer policy for detect_intent_conflicts. 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.

What MCP server provides detect_intent_conflicts? +

detect_intent_conflicts is provided by the Kawa Code MCP server (kawacode-ai/kawa.mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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