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agent-rate-limit-strategy

Control LLM spend and Apex governor exposure for high-traffic Agentforce agents via per-user token budgets and graceful fallback when the budget is exhausted. NOT for reducing tokens per conversation in the first place — use agentforce/agentforce-cost-optimization. NOT for API rate-limiting of Salesforce REST endpoints — use integration/api-governance-and-rate-limits.

The English summary is being prepared. Showing the original description.

PranavNagrecha/AwesomeSalesforceSkills
Works withSalesforce

Run score Not tested

See how to install

Files included (7)

  • SKILL.md3.7 KB
  • references/examples.md5.3 KB
  • references/gotchas.md868 B
  • references/llm-anti-patterns.md7.1 KB
  • references/well-architected.md2.1 KB
  • scripts/check_agent_rate_limit_strategy.py940 B
  • templates/agent-rate-limit-strategy-template.md552 B

SKILL.md (original)

Review the instructions the agent will receive before you install.

Agent Rate Limit Strategy

Agentforce exposes internal LLM quotas indirectly — you hit them as platform 503s with no forward signal. This skill builds a client-side budget gate in front of the agent: per-user token ledger, CMDT-driven thresholds, and a graceful fallback when the budget is exhausted.

Recommended Workflow

  1. Define budget: tokens/user/hour, tokens/tenant/day. Persist in Agent_Rate_Limit__mdt per-persona.
  2. In the channel entry point (LWC wrapper or Connect API), call a BudgetService.checkAndConsume(userId, estTokens) before dispatching to the agent.
  3. Log consumption via Platform Event Agent_Token_Consumed__e — the subscriber rolls into a User_Token_Ledger__c aggregate.
  4. When the budget is exhausted, render the fallback UX (human handoff / retry-after message) instead of calling the agent.
  5. Dashboard: p50/p95 consumption per persona, budget exhaustion count, tokens/turn — page SRE when exhaustion >1%.

Key Considerations

  • Estimate tokens conservatively from input length (chars/4) before the call; reconcile after.
  • Ledger is eventually consistent — use the Platform Event pattern, not synchronous DML.
  • Fallback UX must be pre-approved; a generic 'try again later' erodes trust.

Worked Examples (see references/examples.md)

  • Budget service sketch — 100 Service reps use agent summarization; one rep loops a bad input 500x.
  • Graceful fallback — Budget exhausted mid-conversation.

Common Gotchas (see references/gotchas.md)

  • Estimating tokens from chars misses long RAG context — Estimate says 500 tokens; reality is 5000 after grounding.
  • Platform Event volume limits — High-traffic agent saturates your 24h PE quota.
  • Ledger bucket skew — Timezone boundary resets at midnight UTC, users see it mid-afternoon locally.

Top LLM Anti-Patterns (full list in references/llm-anti-patterns.md)

  • Trusting Agentforce to rate-limit for you — it only fails loudly on hard limits.
  • Hard-coded tokens/minute without per-persona CMDT — cannot respond to traffic shifts.
  • Synchronous ledger DML per turn — blows DML limits.

Official Sources Used

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