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.
npx agentmods add skills/error505/flockion_ai_engineering/cost-controlnpx skills add error505/Flockion_AI_Engineering --skill cost-controlgit clone --depth 1 https://github.com/error505/Flockion_AI_EngineeringWrote 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.
[](https://agentmods.dev/skills/error505/flockion_ai_engineering/cost-control)<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>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.
| Model | Per session | Once 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 |
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.
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?
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.
- 3d ago First seen · 146 lines · 65 tokens per session scan A 4ee572f748c9
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.
Other skills, from other repositories
frontier
Execute any task at frontier quality. Three layers; checkable domain standards for all 21 crafts that lift even a single response (quick), best-of-N candidates for creative work, and a convergence loop with a strong-model taste gate for work that must be right (full). Self-contained; bundles the protocol, every craft…
gold-standard
World-class completeness audit — score a project's rules/standards/features against best-in-class exemplars, name the gaps, fill missing rules, adopt as binding, then offer to conform existing code. Triggers on keywords: "/gold-standard", "gold-standard", "audit rules", "are we world-class", "fill gaps", "complete our…
drift-canary
Compatibility and schema drift canary — checks for database schema migration safety, breaking API contract changes, serializable payload mismatches, and backward compatibility drift. Triggers on keywords: "/drift-canary", "drift-canary", "contract drift", "breaking changes". Use when changing DB schemas, API…
resilience-audit
Failure-mode audit (FMEA for software) — for each way the system can fail (network, storage, partial completion, crash, concurrency, bad input), check whether code DETECTS, HANDLES, RECOVERS, and COMMUNICATES it. Triggers on: "/resilience-audit", "resilience-audit", "FMEA audit". Use when touching network, storage…
rot-canary
Code-health scan — dead code, bug-prone logic, resource leaks, concurrency bugs, silent failures, input-boundary issues, doc rot. Triggers on: "/rot-canary", "rot-canary", "code-health" (legacy aliases: "/rotcanary", "rotcanary"). Auto-runs at session end on touched files (QUICK, report only) via platform hooks …
source-grounding
Verify version-sensitive facts against live authoritative sources before asserting them in code or answers. Triggers on: "/source-grounding", "source-grounding", "sourcing". Standing rule — always active via CLAUDE.md. Invoke for deep verification work (API signatures, CVEs, model IDs, auth flows, deprecated patterns…