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 avmnu-sng/sutra --skill agent-orchestrationgit clone --depth 1 https://github.com/avmnu-sng/sutraWrote 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/avmnu-sng/sutra/agent-orchestration)<a href="https://agentmods.dev/skills/avmnu-sng/sutra/agent-orchestration"><img src="https://agentmods.dev/badge/skills/avmnu-sng/sutra/agent-orchestration/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/avmnu-sng/sutra/agent-orchestration"><img src="https://agentmods.dev/badge/skills/avmnu-sng/sutra/agent-orchestration.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 | $0.00033 | $0.01329 |
| Opus 5 | $0.00016 | $0.00665 |
| Sonnet 5 | $0.00007 | $0.00266 |
| Haiku 4.5 | $0.00003 | $0.00133 |
Grade A, and why
agent-orchestration 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 9d 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 — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent orchestration
Subagents are a force multiplier for mechanical, parallelizable, and verifiable work. They are not a substitute for judgment. Treat every agent's output as evidence you must verify -- not as a finished deliverable. You own every finding you publish, regardless of which agent produced it.
When to use
Delegate work that is well-specified, has a checkable answer, and does not depend on holding the whole problem in your head:
- Mechanical tracing. Follow one call path, one data flow, or one config chain to its end. "Trace how a request reaches the persistence layer."
- Point verification. Confirm one claim at one location. "Does function
parse_headeratsrc/net/http.rbhandle a missing content-length?" - Search and aggregation. Find every call site, collect all matches of a pattern, tally occurrences across a tree.
- Parallel independent reads. Fan out N agents to read N files or modules for coverage when the reads do not depend on each other.
- Validation. Check one agent's claim against the code, or cross-check two agents that touched the same surface.
Rule of thumb: if you can state the question, the exact place to look, and the shape of a correct answer, an agent can do it.
When not to use
Keep these yourself. Delegating them produces confident, wrong, or shallow output:
- Architecture and design thinking. Agents analyze components in isolation. They miss cross-component interactions, shared-state coupling, and cascading effects. A design decision lives in the seams between parts, which no single-component agent sees.
- Trade-off weighing. Agents will list pros and cons, but they do not weigh them with real numbers (latency budgets, memory ceilings, blast radius, team cost). A list is not a decision.
- Anything session-dependent. Agents start fresh with no memory of this session -- prior decisions, constraints you discovered, why option B was already ruled out. If the answer depends on context you built up, the agent cannot reconstruct it.
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.
- 9d ago First seen · 119 lines · 33 tokens per session scan A af46cccf0715
agent-orchestration is a skill published in the GitHub repository avmnu-sng/sutra (2 stars, last pushed 1mo ago), licensed MIT. It adds 33 tokens to every session and 1,329 once invoked, about $0.0002 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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