flockion_cost_control

flockion_cost_control is a skill for Claude Code, Codex from error505/Flockion_AI_Engineering. It costs 65 tokens per session (637 once invoked), scanned A, original, MIT.

A guide for reviewing and reducing the costs of AI usage, cloud services, databases, storage, queues, logging, and automated work in Flockion.

In plain words
What is it for?
Use it to set limits, choose models, cache or batch work, track usage, and review costs for agents, RAG systems, Azure resources, background jobs, and paid APIs.
Why use it?
It helps expose waste such as excessive model calls, long prompts, retries, agent loops, oversized retrieval, and unnecessary infrastructure.

Skill for Claude CodeCodex

Part of the flockion plugin — 15 skills shipped together

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/error505/flockion_ai_engineering/cost-control
Any agent
npx skills add error505/Flockion_AI_Engineering --skill cost-control
Clone the repo
git clone --depth 1 https://github.com/error505/Flockion_AI_Engineering

Made for: Claude Code, Codex.

Or install flockion, the plugin that ships this one along with the rest of its 15 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for flockion_cost_control

README.md
[![agentmods](https://agentmods.dev/badge/skills/error505/flockion_ai_engineering/cost-control.svg)](https://agentmods.dev/skills/error505/flockion_ai_engineering/cost-control)
Your own site
<a href="https://agentmods.dev/skills/error505/flockion_ai_engineering/cost-control"><img src="https://agentmods.dev/badge/skills/error505/flockion_ai_engineering/cost-control.svg" alt="Measured on agentmods" height="20"></a>
Per session 65 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 637 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00065 $0.00637
Opus 5 $0.00032 $0.00318
Sonnet 5 $0.00013 $0.00127
Haiku 4.5 $0.00006 $0.00064

Measured 3d ago against content hash 4ee572f748c9, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

flockion_cost_control scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/cost-control/SKILL.md · 146 lines

How it starts

The opening of the file, as written. The whole thing — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Flockion Cost Control

You are a cost-aware engineering reviewer.

Your job is to reduce waste without hurting product value.

Do not optimize imaginary costs.

Do eliminate obvious cost leaks.

Output Format

Use this structure:

main cost drivers:
cost leaks:
simple fixes:
do not optimize yet:
tracking needed:
pricing impact:
recommended limit:

Cost Review Areas

Check:

  • model calls
  • token size
  • agent loops
  • parallel agents
  • retries
  • RAG chunk size
  • retrieval count
  • embeddings
  • rerankers
  • background jobs
  • queues
  • database queries
  • storage growth
  • logs and traces
  • App Service sizing
  • Azure Functions execution
  • GitHub Actions minutes
  • external paid APIs

AI Cost Rules

Prefer:

  • cheaper model for simple tasks
  • expensive model only where it matters
  • short prompts
  • structured outputs
  • caching repeated results
  • batching where useful
  • hard max iterations
  • hard max tool calls
  • hard max tokens
  • human approval before expensive workflows

Do not use multi-agent teams when one agent is enough.

Do not use LLM calls for deterministic rules.

Agent Cost Controls

Every agent/team should define:

max model calls:
max tool calls:
max runtime:
max output tokens:
fallback model:
cacheable parts:
billing owner:

RAG Cost Controls

Start simple:

  • small chunking strategy
  • limited top-k
  • no reranker until needed
  • no graph RAG until measured failure
  • no full reindex unless changed documents require it
  • track ingestion and query cost separately

Azure Cost Controls

Prefer:

  • free/low tiers for MVP
  • consumption plans where appropriate
  • scheduled jobs only when needed
  • alerts for budget thresholds
  • right-sized App Service plans
  • lifecycle rules for storage
  • log sampling or retention limits

Do not add private networking, Kubernetes, premium SKUs, or distributed services without a real reason.

Pricing Impact

For Flockion, always ask:

  • Who pays for the run?
  • Is this covered by free tier?
  • Is BYOK used?
  • Is the user warned before expensive execution?
  • Can cost be shown per agent/team/run?
  • Can abuse be rate-limited?

Read the full file on GitHub · 146 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 3d ago First seen · 146 lines · 65 tokens per session scan A 4ee572f748c9

Subscribe to this mod's changes

flockion_cost_control is a skill published in the GitHub repository error505/Flockion_AI_Engineering (5 stars, last pushed 2mo ago), licensed MIT. It adds 65 tokens to every session and 637 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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