tengu_v3_intel_pnl_attribution
Daily PnL track record for the paper book, Carhart 4-factor-decomposed. Snapshotted nightly. Returns rows[] of trading days with per-row gross/net return in basis points, transaction cost, turnover, plus the Carhart factor contributions (MKT-RF, SMB, HML, UMD) and residual alpha — the institution...
This record as markdown: /tools/tengu-mcp/tengu-v3-intel-pnl-attribution.md
What tengu_v3_intel_pnl_attribution does on Tengu
AI agents call tengu_v3_intel_pnl_attribution to retrieve information from Tengu without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
days | string | — |
Parameters from the server's own tool schema.
Why tengu_v3_intel_pnl_attribution is rated Low
Even though tengu_v3_intel_pnl_attribution only reads data, uncontrolled read access leaks sensitive information and racks up API costs: an agent caught in a retry loop can make thousands of calls a minute without anyone noticing.
Attacks that exploit this kind of access
The rule that runs tengu_v3_intel_pnl_attribution safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Tengu, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For tengu_v3_intel_pnl_attribution, this is the rule to start with:
tengu_v3_intel_pnl_attribution is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Tengu, apply this rule, and every tengu_v3_intel_pnl_attribution call is checked against it from then on.
Questions about tengu_v3_intel_pnl_attribution
Daily PnL track record for the paper book, Carhart 4-factor-decomposed. Snapshotted nightly. Returns rows[] of trading days with per-row gross/net return in basis points, transaction cost, turnover, plus the Carhart factor contributions (MKT-RF, SMB, HML, UMD) and residual alpha — the institutional skill measure that strips market/size/value/momentum beta. Window aggregate: mean daily bps, hit rate, annualised Sharpe, cumulative net + alpha. Default 30 trading days; query ?days=N (bounded to 365). Use this to ground any track-record claim the chat makes — e.g. 'our paper book made +29 bps yesterday, +111 bps alpha contribution'. 1h cache. It is categorised as a Read tool in the Tengu MCP Server, which means it retrieves data without modifying state.
tengu_v3_intel_pnl_attribution accepts 1 parameter: days. The full parameter table on this page comes from the server's own tool schema.
Register the Tengu MCP server in PolicyLayer and add a rule for tengu_v3_intel_pnl_attribution: 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 Tengu. Nothing to install.
tengu_v3_intel_pnl_attribution 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 tengu_v3_intel_pnl_attribution 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 tengu_v3_intel_pnl_attribution. 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.
tengu_v3_intel_pnl_attribution is provided by the Tengu MCP server (Hlobo-dev/tengu-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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