| name | agent-budget |
| description | Write the spend spec for an agentic workflow — per-stage model tiers, token caps with hard abort rules, a graceful-degradation order, and cost-per-outcome as the governing metric. Use when the user asks what an agent loop or multi-agent workflow should be allowed to spend, wants token/cost budgets and caps for AI automation, or got a surprise bill from an agent fleet. |
agent-budget
An unbudgeted agent loop is a runaway-cost incident with an architecture diagram. This skill produces the budget spec that governs an agentic workflow: what each stage may spend, on which tier of model, what happens at the cap, and — the number that actually matters — what one outcome costs. Pairs with agent-loop-design (the caps land in its loop spec) and subagent-design (the fleet line lands in its role cards); the tier vocabulary is this repo's own light/standard/heavy routing abstraction, so the spec ports across providers. Infra spend (compute, storage, egress) is capacity-cost-model's domain — this skill budgets the tokens.
How to respond
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Pin the outcome unit and the workflow's stages. Ask at most 2 questions, spent on: "what is one successful outcome?" (a merged PR, a triaged ticket, a verified report — the denominator every cost divides by) and "what does a typical run look like today?" (stages, rounds, models — or "not built yet", which makes this a design-time budget, the cheap time to write one). Non-interactive run (no user to ask): derive both from the input and tag [assumption]; no outcome unit derivable → emit BLOCKED: need the workflow and its outcome unit.
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Assign each stage the cheapest adequate tier — light / standard / heavy, per the routing rule of thumb: light for mechanical extraction and formatting, standard for most generation, heavy only where the hard thinking is the value (adversarial verification, weighted judgment) — and heavy stages are never downgraded to save money; they're where the money buys correctness. Every tier assignment carries a one-line rationale. The classic misallocation runs both directions: frontier models formatting JSON, and — worse — the cheap model doing the verify pass that exists to catch the cheap mistakes.
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Set three numbers per stage in templates/budget-spec.md: expected spend per run (estimate honestly, tag [assumption] until measured), cap (the hard stop — 3–5× expected, tighter for unattended loops), and on-cap action (abort-and-escalate, or degrade — never "continue and warn"; a warning nobody is watching is a continue). State each as tokens and approximate money — tokens are what the harness enforces, but money is the only unit that sums across tiers, so all cap comparisons happen in currency. A stage that fans out per item carries two caps: a per-item cap (that item fails to the report's needs-human list; the rest continue) and a stage-wide cap. Then the run-level cap for the whole workflow — in currency, less than the sum of stage caps: every stage simultaneously hitting its cap is not a run to finish, it's an anomaly to stop.
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Write the degradation ladder — what gives, in order, when spend pressure hits: first narrow scope (fewer items per run), then reduce parallelism (smaller fleet, slower wall-clock), then cut non-verification stages (skip the polish pass), and last — never — verification. Skipping verify to save tokens converts a cost problem into a correctness problem at the exact moment quality is already under pressure; a workflow that can't afford its verifier can't afford to run. State each rung's trigger and who flips it.
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Make cost-per-outcome the governing metric. Total tokens is noise; spend ÷ successful outcomes is the number with meaning — a loop that gets cheaper per run but passes fewer runs got more expensive. Give it a target and a review threshold, and put beside it the comparison line: what the same outcome costs today (an hour of an engineer's time, the manual process) — a $4 triaged ticket is expensive against 60 seconds of a human's glance and cheap against twenty minutes of one; without the line, nobody can say which.
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Add measurement and emit. Spend logged per run per stage (tagged by stage name, feeding the loop spec's telemetry row); weekly review of cost-per-outcome and cap-hit counts by a named role; alert on cap-hit rate rising (the leading indicator of drift — inputs grew, a prompt regressed, or a model changed under you) and on any run breaching the run-level cap (that's an incident, not a line item). Emit the spec in one message: stage table, run cap, degradation ladder, cost-per-outcome with comparison line, measurement plan. Flag every [assumption] estimate as the calibration backlog — after ~20 real runs, expected values stop being guesses. Hand off: the caps → agent-loop-design's loop spec; per-agent tiers → subagent-design's role cards; the verifier's quality gate → llm-eval-harness.
Useful references in this skill
Quality bar
- The outcome unit is named and every cost in the doc divides by it.
- Every stage has tier + rationale + three numbers (expected, cap, on-cap action). No stage rides free.
- Heavy tiers survive. No verification or judgment stage was downgraded to make the total look better.
- Caps are hard. Every on-cap action is abort or degrade — "warn and continue" appears nowhere.
- The run cap is less than the sum of stage caps, and the doc says why.
- Verification is last on the degradation ladder, explicitly.
- The comparison line exists — cost-per-outcome sits next to what the outcome costs without the agents.
- Estimates are tagged.
[assumption] until measured; the calibration step is scheduled, not implied.
When to use this skill
- ✅ "What should this agent workflow be allowed to spend?" — at design time, the cheap time
- ✅ A surprise token bill arrived — retrofit caps and a degradation ladder
- ✅ An
agent-loop-design or subagent-design spec needs its budget line filled in
- ✅ "Is this automation actually cheaper than doing it by hand?" — build the comparison line
When NOT to use this skill
- ❌ Infra/cloud cost modeling (compute, storage, egress) —
capacity-cost-model
- ❌ Choosing a model tier for a single skilldrop skill — that's
model-routing.json's table, already decided
- ❌ Designing the loop or the fan-out itself —
agent-loop-design / subagent-design; this skill prices what they draw
- ❌ Negotiating provider contracts or rate limits — procurement, not a spec
Anti-patterns to avoid
- ❌ Budget-free loops. "We'll see what it costs" means the invoice is the monitoring system.
- ❌ Warn-and-continue caps. A cap whose breach action is a log line is a number, not a cap.
- ❌ Skimping the verifier. Downgrading or skipping verification under spend pressure — the false economy that ships fleet-speed garbage precisely when scrutiny dropped.
- ❌ Token vanity metrics. Celebrating "20% fewer tokens" while cost-per-successful-outcome rose because pass rates fell.
- ❌ Frontier-everything. The orchestrator's model formatting JSON at heavy-tier prices because nobody assigned tiers per stage.
- ❌ Missing comparison line. A cost-per-outcome with nothing beside it can justify anything or condemn anything.
- ❌ Estimates that never graduate.
[assumption] numbers still governing caps six months and a thousand runs later.
