Update the project's feature catalog from its recorded intents. Additively groups any intents that are not yet assigned to a feature into the running catalog (an incremental "extend"), without disturbing existing features. The feature catalog is the high-level "what does this project actually do?...
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AI agents use update_features to create or modify resources in Kawa Code MCP. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.
Without a policy, an AI agent could call update_features repeatedly, creating or modifying resources faster than any human could review. PolicyLayer's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach Kawa Code MCP.
Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.
{
"version": "1",
"default": "deny",
"tools": {
"update_features": {
"limits": [
{
"counter": "update_features_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}See the full Kawa Code MCP policy for all 21 tools.
These attack patterns abuse exactly the kind of access update_features gives an agent. Each links to the full case and the policy that stops it:
Other write tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.
Update the project's feature catalog from its recorded intents. Additively groups any intents that are not yet assigned to a feature into the running catalog (an incremental "extend"), without disturbing existing features. The feature catalog is the high-level "what does this project actually do?" view, derived from the repo's intents. When to use: - After recording or completing intents, to keep the feature list current. - On demand, when you want the catalog refreshed with recent work. Behavior: - Additive only — never deletes or re-derives existing features. - Intents already assigned to a feature are skipped; only unassigned ones are processed. - Runs in the Kawa Code desktop app and returns the resulting feature count.. It is categorised as a Write tool in the Kawa Code MCP MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Kawa Code MCP server in PolicyLayer and add a rule for update_features: 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.
update_features is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the update_features 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 update_features. 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.
update_features 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.
Deterministic rules across all 21 Kawa Code MCP tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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