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/xiaolai/nlpm/orchestrationnpx skills add xiaolai/nlpm --skill orchestrationgit clone --depth 1 https://github.com/xiaolai/nlpmWrote 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/xiaolai/nlpm/orchestration)<a href="https://agentmods.dev/skills/xiaolai/nlpm/orchestration"><img src="https://agentmods.dev/badge/skills/xiaolai/nlpm/orchestration.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 | $0.00042 | $0.02908 |
| Opus 5 | $0.00021 | $0.01454 |
| Sonnet 5 | $0.00008 | $0.00582 |
| Haiku 4.5 | $0.00004 | $0.00291 |
Grade A, and why
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 4d 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 — 371 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Orchestration
Scope: covers multi-agent workflow design. For individual agent authoring, see [[writing-agents]]. For plugin architecture, see [[writing-plugins]].
1. Four Orchestration Patterns
Pattern A: Parallel Dispatch
Multiple agents run simultaneously on independent work. A command dispatches them via the Task tool and synthesizes results.
Command dispatches via Task:
|-- agent-1 (analyzes security)
|-- agent-2 (analyzes performance)
|-- agent-3 (analyzes architecture)
--> Command synthesizes all results into final report
Use when: agents don't depend on each other's output.
Real examples:
- grill plugin: 6 review agents analyze code from different angles in parallel
- docs-guardian: 4 agents (staleness, accuracy, coverage, quality) run simultaneously
Implementation pattern in command body:
## Execution
1. Dispatch the following agents in parallel using Task:
- security-agent: analyze for vulnerabilities
- performance-agent: analyze for bottlenecks
- architecture-agent: analyze for structural issues
2. Collect all agent outputs
3. Synthesize into a unified report with cross-references
Key decisions:
| Decision | Recommendation |
|---|---|
| Max parallel agents | 6 (diminishing returns above this) |
| Timeout per agent | 120 seconds for sonnet, 300 for opus |
| Failure handling | Continue with other agents if one fails |
| Result merging | Deduplicate findings that appear in multiple agents |
Pattern B: Sequential Pipeline
Each stage feeds into the next. Output of stage N is input to stage N+1.
parse --> chunk --> summarize --> QC --> output
Use when: each stage depends on the previous stage's output.
Real examples:
- reading-assistant: parse PDF -> chunk content -> summarize chunks -> QC summaries -> output
- tdd-guardian: discover tests -> run tests -> check coverage -> analyze failures -> report -> enforce
Implementation pattern:
## Execution
### Phase 1: Parse (haiku)
1. Scan input files
2. Extract structured content
3. Output: parsed data as JSON
### Phase 2: Process (sonnet)
4. Receive parsed data from Phase 1
5. Analyze and transform
6. Output: processed results
### Phase 3: QC (sonnet)
7. Verify Phase 2 output meets quality bar
8. Output: pass/warn/fail verdict
### Phase 4: Output
9. If QC passed: format and deliver final report
10. If QC failed: report failures and stop
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.
- 4d ago First seen · 371 lines · 42 tokens per session scan A 9f040fe0beb4
orchestration is a skill published in the GitHub repository xiaolai/nlpm (134 stars, last pushed today), licensed ISC. It adds 42 tokens to every session and 2,908 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 2026-08-30.
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