Authenticated — returns stages in the caller's active course where recorded evidence is thin relative to the stage's principle requirements. Each thin stage carries the missing principle slugs + a short diagnostic so the caller can suggest the user record concrete evidence. WHEN TO CALL: when the...
Risk signalsBulk/mass operation — affects multiple targets
Part of the AI Design Blueprint server.
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AI agents call me.coaching_context to retrieve information from AI Design Blueprint 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 me.coaching_context 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": {
"me.coaching_context": {}
}
}See the full AI Design Blueprint policy for all 24 tools.
These attack patterns abuse exactly the kind of access me.coaching_context 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.
Authenticated — returns stages in the caller's active course where recorded evidence is thin relative to the stage's principle requirements. Each thin stage carries the missing principle slugs + a short diagnostic so the caller can suggest the user record concrete evidence. WHEN TO CALL: when the user asks 'what should I work on next' or 'what's weak in my Blueprint progress'; before suggesting which guide/example to consult. Pair with me.add_evidence to close gaps. WHEN NOT TO CALL: to lecture the user on principles they have already satisfied; on every conversation turn (state changes only when evidence is added). BEHAVIOR: read-only, idempotent. Auth: Bearer <token> (any plan). Returns thin_stages list with stage slug, course slug, missing principles, evidence_count, and a coaching_note.. It is categorised as a Read tool in the AI Design Blueprint MCP Server, which means it retrieves data without modifying state.
Register the AI Design Blueprint MCP server in PolicyLayer and add a rule for me.coaching_context: 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 AI Design Blueprint. Nothing to install.
me.coaching_context 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 me.coaching_context 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 me.coaching_context. 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.
me.coaching_context is provided by the AI Design Blueprint MCP server (https://aidesignblueprint.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 24 AI Design Blueprint tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
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