Compute the user's TAOS assessment scores from the numeric answers collected during the assessment conversation. Takes the per-question answers (each 1 to 5) and per-domain expertise ratings, and returns the user's dependency risk, growth potential, AI literacy, expertise summary, and overall TAO...
Part of the Talent-Augmenting Layer server.
Free to start. No card required.
AI agents call talent_assess_score to retrieve information from Talent-Augmenting Layer 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 talent_assess_score 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": {
"talent_assess_score": {}
}
}See the full Talent-Augmenting Layer policy for all 15 tools.
These attack patterns abuse exactly the kind of access talent_assess_score 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.
Compute the user's TAOS assessment scores from the numeric answers collected during the assessment conversation. Takes the per-question answers (each 1 to 5) and per-domain expertise ratings, and returns the user's dependency risk, growth potential, AI literacy, expertise summary, and overall TAOS readiness score, with plain-language interpretations and recommended coaching calibration. Call this once all assessment questions have been answered, then pass the result to talent_assess_create_profile.. It is categorised as a Read tool in the Talent-Augmenting Layer MCP Server, which means it retrieves data without modifying state.
Register the Talent-Augmenting Layer MCP server in PolicyLayer and add a rule for talent_assess_score: 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 Talent-Augmenting Layer. Nothing to install.
talent_assess_score 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 talent_assess_score 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 talent_assess_score. 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.
talent_assess_score is provided by the Talent-Augmenting Layer MCP server (https://proworker-hosted.onrender.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 15 Talent-Augmenting Layer tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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