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 skills add yeaight7/agent-powerups --skill agent-runtime-patternsgit clone --depth 1 https://github.com/yeaight7/agent-powerupsWrote 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/yeaight7/agent-powerups/agent-runtime-patterns)<a href="https://agentmods.dev/skills/yeaight7/agent-powerups/agent-runtime-patterns"><img src="https://agentmods.dev/badge/skills/yeaight7/agent-powerups/agent-runtime-patterns/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/yeaight7/agent-powerups/agent-runtime-patterns"><img src="https://agentmods.dev/badge/skills/yeaight7/agent-powerups/agent-runtime-patterns.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00030 | $0.00636 |
| Opus 5.5 | $0.00012 | $0.00254 |
| Sonnet 5.5 | $0.00006 | $0.00127 |
| Haiku 4.5 | $0.00003 | $0.00064 |
Grade A, and why
agent-runtime-patterns 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 1mo 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 — 55 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Runtime Patterns
When to use
- Optimizing a slow or over-spending agent loop (too many tool calls, high token use).
- Designing multi-agent orchestration topology for a new workflow.
- Managing MCP session lifecycle for experimental data-layer sessions.
- Reducing redundant search or file-read loops.
Core Patterns
| Pattern | Use when | Avoid when |
|---|---|---|
| Direct execution | Single agent, clear scope, no subagent benefits | Task genuinely requires parallel sub-agents or specialized routing |
| Routing | Input type determines which specialized agent to invoke | Agents share context and can't be isolated |
| Chaining | Output of A is strict input of B | Agents need to share partial context |
| Orchestrator-worker | Parallel independent subtasks with a coordinator | Tasks are tightly coupled or sequential |
| Agents-as-tools | Callable child agent inside a parent's tool loop | The child needs user interaction |
Knowledge Cards
A card is a compact, high-signal instruction block — typically 3–10 lines — for a specific operation. Cards are preferable to loading full documentation into context.
Good card: step sequence + key constraint + example invocation. Bad card: copied README sections, multiple unrelated topics in one block.
Pack cards for the current task only. Swap cards between phases rather than accumulating them.
Workflow
- Identify the bottleneck — measure before optimizing: count tool calls, token usage, and latency. Name the specific slow or expensive step.
- Choose the right pattern — use the table above. Default to direct execution; add orchestration only when simpler approaches are insufficient.
- Pack knowledge as cards — replace large prompt docs with targeted 5–10 line cards per operation.
- Bound search loops — cap retries (e.g., max 3 search attempts), normalize query construction, prefer a dedicated search subagent over inline ad-hoc loops.
- Model MCP sessions explicitly — for experimental sessions: track create/delete lifecycle, request
_metasession IDs, handle missing-session errors without silent retries. - Measure after — compare latency, tool-call count, token use, and task success rate before/after.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 55 lines · 30 tokens per session scan A 38ae075e5630
agent-runtime-patterns is a skill published in the GitHub repository yeaight7/agent-powerups (8 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 30 tokens to every session and 636 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-14.
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