CALL THIS to record DECISIONS and CONVENTIONS. WHEN TO CALL: A. CONFLICT RESOLUTION — STOP IMMEDIATELY when any of these occur: - User says: "don't use X", "use Y instead", "prefer", "switch to". - During planning: user's request or your proposal differs from AI_README conventions. - During plann...
Risk signalsAccepts raw HTML/template content (operations[].content)
Part of the Ai Readme server.
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AI agents use update_ai_readme to create or modify resources in Ai Readme. 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_ai_readme 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 Ai Readme.
Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.
{
"version": "1",
"default": "deny",
"tools": {
"update_ai_readme": {
"limits": [
{
"counter": "update_ai_readme_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}See the full Ai Readme policy for all 6 tools.
These attack patterns abuse exactly the kind of access update_ai_readme 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.
CALL THIS to record DECISIONS and CONVENTIONS. WHEN TO CALL: A. CONFLICT RESOLUTION — STOP IMMEDIATELY when any of these occur: - User says: "don't use X", "use Y instead", "prefer", "switch to". - During planning: user's request or your proposal differs from AI_README conventions. - During planning: user approves a plan that contradicts AI_README. - User overrides a convention mid-task (even casually, e.g. 'just use X here'). - DO NOT continue planning or coding. Call update_ai_readme first, then resume. B. ARCHITECTURAL DECISIONS (during planning/implementation): - You chose a design pattern (e.g., repository pattern, factory, singleton). - You decided on API structure (REST paths, error format, response shape). - You established naming conventions (files, functions, variables). - You created new abstractions (utilities, hooks, services, types). - You set up error handling strategy or validation approach. - You introduced a new dependency or integration pattern. C. IMPLEMENTATION PATTERNS (after writing code): - You created a reusable pattern others should follow. - You established a file/folder structure for a new feature. - You made decisions that affect future development. D. MISSING / UNDOCUMENTED (during get_context or code review): - AI_README is missing a convention that is ALREADY USED in 2+ existing files. - A pattern exists in code but not in AI_README — record it so future code follows it. - Do NOT record one-off choices or speculative future patterns. RULE: If a decision will affect MORE THAN ONE FILE or FUTURE CODE → RECORD IT. WORKFLOW: 1. get_context (read current conventions). 2. Make decision or detect conflict. 3. update_ai_readme (record the decision). 4. Continue with implementation. Content Rules: - Extremely concise (< 400 tokens). - Only actionable conventions (tech, naming, patterns, infrastructure patterns, testing patterns). - NO explanations or examples. It is categorised as a Write tool in the Ai Readme MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Ai Readme MCP server in PolicyLayer and add a rule for update_ai_readme: 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 Readme. Nothing to install.
update_ai_readme 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_ai_readme 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_ai_readme. 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_ai_readme is provided by the Ai Readme MCP server (ai-readme-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 6 Ai Readme tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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