How does this skill prevent budget overruns compared to standard per-agent caps?

It does not enforce anything at runtime. It audits your orchestration code for the gap where every agent has its own cap but nothing adds the spend up across the swarm, and for missing swarm-wide kill switches, racy spend checks and spawn paths a cap never sees. The report tells you which fix closes each gap.

Which agent frameworks and programming languages does the swarm budget gate support?

LangGraph, CrewAI, AutoGen, custom recursive-delegation harnesses and Claude Agent SDK subagent spawning. The skill's reference ledger implementation is Python; other languages can be audited by the same rules, but the skill's worked examples and reference code are not written for them.

Does this skill require me to install a runtime monitoring agent or modify my production environment?

No, this is a static analysis tool designed for pre-deployment audits; it identifies logic flaws and provides remediation snippets rather than intercepting live API calls.

What exactly is included in the purchase of the swarm budget gate skill?

The skill instructions and one dated reference comparing existing budget tools (AgentGuard, SupraWall, Cycles). Your agent produces a ranked audit that traces every spawn point in your repo and checks whether spend is pooled and kill-switchable across the swarm. The paid tier adds a recommended primitive for each gap and generated code scoped to your codebase. There are no bundled scripts or tools.

Are there any scenarios where the static audit might miss a potential spawn point?

The audit cannot fully trace dynamic agent construction triggered by external webhooks or third-party plugin registries that are not defined within the local repository.

Works with the AI tools you already use

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swarm budget gate

Static audit for multi-agent swarm orchestration to prevent budget overruns caused by recursive spawns and racy ledgers.

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swarm budget gate

Example session with this skill installed

Audit this LangGraph repo for swarm-level budget safety. We have a $5 cap on each agent loop, so it should be fine. Check if we need a shared ledger for the parallel branches.

Read your context and instructions
Compiled the swarm budget gate
Generated the document

I have completed the static audit of the LangGraph orchestration code. The swarm currently lacks a shared ledger, creating a significant financial unboundedness risk despite individual agent caps.

Swarm Budget Audit Report

Metric	Status	Finding
Verdict	FAIL	Financial ceiling is unenforced across concurrent branches.
Spawn Inventory	INCOMPLETE	Found 3 explicit spawns; recursive delegation in `tools/researcher.py` is untraceable.
Shared Ledger	ABSENT	Each agent tracks local `state["cost"]` with no global aggregation.
Kill-Switch	PROCESS-BOUND	Signal handler only halts the main thread; sub-processes will persist.

Financial Risk Arithmetic

Per-Agent Cap: $5.00
Max Concurrent Agents: 10 (per config.yaml thread pool)
Theoretical Ceiling: $50.00 per execution cycle.

Gap: The orchestrator does not sum spend across branches. If 10 agents run in parallel, the swarm spend is 10x the assumed $5 limit.

Code Analysis: Race Condition Risk

The current implementation in nodes/execute.py uses a read-then-write pattern:


# FAIL: Read-then-write race condition
if current_spend < MAX_BUDGET:
    result = await agent.run()
    update_spend(result.cost)

Under concurrent dispatch, multiple agents will read the same current_spend value before any have written their updates, bypassing the $5 cap entirely.

Next steps

Implement a reservation-based ledger using an atomic increment (e.g., Redis INCRBY or SQL row lock).
Move the kill-switch flag to a shared durable store like a file or database.
Explicitly pass a shared BudgetContext object to the researcher.py tool to track recursive costs.

swarm-budget-gate.pdf

PDF · document

Generated

Example file from a real run - the skill writes it into your workspace.

Connects securely to your tools. The creator never sees your data.

What you get

Audit recursive delegation for hidden spend paths.Verify atomic ledger logic to prevent budget races.Calculate theoretical spend ceilings for parallel agent fleets.Identify process-dependent kill switches that fail during crashes.

About this skill

Multi-agent swarms can route around individual agent caps by spawning recursive subagents or parallel branches. If your orchestrator lacks a shared ledger, the total bill is the sum of every cap across every agent spawned, which often lacks a hard ceiling. This skill provides a static audit of orchestration code to identify these financial blind spots before deployment.

What it does

Spawn point inventory identifies every location where agents are instantiated, including recursive delegation and tool-triggered spawns.
Ledger atomicity check verifies if shared budget tracking uses reservation-based atomic operations to prevent races during concurrent dispatches.
Kill-switch validation audits whether a swarm-wide halt persists if the primary orchestrator process crashes or is killed.
Theoretical ceiling calculation computes the actual financial risk by multiplying per-agent caps by maximum concurrent agent counts.
Remediation mapping recommends specific runtime primitives or generates scoped ledger snippets to close identified gaps.

How it works

Run the Spawn Inventory command to grep the entire repository for framework-specific instantiation primitives.
Analyze the budget tracking logic to determine if spend is aggregated across all spawn points or isolated per agent.
Test the kill-switch durability against externally stored states rather than local process flags.
Review the final audit report for a PASS, FAIL, or INCOMPLETE verdict based on ironclad concurrency and enumeration rules.

Frameworks & tools

Works with LangGraph, CrewAI, AutoGen, and custom recursive-delegation harnesses. Compatible with Python and TypeScript orchestration layers.

Why this beats prompting it yourself

Generic prompts often overlook the race conditions inherent in concurrent agent dispatches. This skill enforces a strict "reserve-before-execute" logic and repo-wide spawn tracing that prevents agents from bypassing budget gates through retries or tool calls.

Use cases

Auditing a LangGraph swarm for recursive subagent spend before production release.
Investigating budget overruns where individual agents stayed under their local caps.
Designing a race-free shared ledger for a high-concurrency CrewAI implementation.

Known limitations

Does not enforce budgets at runtime. Static analysis cannot fully trace dynamic agent construction from external webhooks or plugin registries.

How to install

Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.

~30 seconds

1
Download the ZIP
Free skills download straight away. Paid skills unlock right after purchase.
2
Unzip into your skills folder
Every agent reads skills from one folder on your machine. Drop the unzipped folder in there.
3
Ask your agent to use it
Restart the agent if it was already running. It picks the skill up automatically - no config needed.

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Click the path to copy it. Create the folder if it does not exist yet.

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swarm budget gate