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/sharpdeveye/maestro/streamlinenpx skills add sharpdeveye/maestro --skill streamlinegit clone --depth 1 https://github.com/sharpdeveye/maestroWhat 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 | $0.00027 | $0.00643 |
| Opus 5 | $0.00014 | $0.00321 |
| Sonnet 5 | $0.00005 | $0.00129 |
| Haiku 4.5 | $0.00003 | $0.00064 |
Grade A, and why
streamline 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 2d 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 — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MANDATORY PREPARATION
Invoke /agent-workflow — it contains workflow principles, anti-patterns, and the Context Gathering Protocol. Follow the protocol before proceeding — if no workflow context exists yet, you MUST run /teach-maestro first. Consult the agent-architecture reference in the agent-workflow skill for complexity assessment and topology simplification.
Reduce complexity without reducing capability. Every component should earn its place.
Streamlining Analysis
For each component, ask:
- Does this add measurable value? If you can't name the specific value, remove it.
- Can this be combined with another component? Merge overlapping responsibilities.
- Is this solving a real problem or an imagined one? Remove speculative complexity.
- Would a simpler alternative work? Prefer simplicity over elegance.
Common Streamlining Targets
Pipeline Steps
- Remove steps that transform data without changing it meaningfully
- Combine sequential steps that could be one prompt
- Eliminate validation steps that duplicate downstream validation
Tool Consolidation
- Merge tools that operate on the same data with different filters
- Remove tools the model never selects (check usage logs)
- Combine read tools with similar signatures
Prompt Simplification
- Remove instructions the model follows by default
- Consolidate redundant constraints
- Shorten few-shot examples to minimum viable length
Configuration Reduction
- Remove config parameters that always use the default
- Hardcode values that never change between environments
- Merge related config into logical groups
Streamlining Report
For each recommendation:
- What to remove/simplify — specific component or code
- Why it's safe — what ensures functionality is preserved
- Expected impact — latency reduction, cost reduction, or maintainability improvement
Complexity Score
| Component | Current | Minimal Viable | Action |
|---|---|---|---|
| Pipeline steps | ? | ? | Remove/merge ? |
| Tools | ? | ? | Consolidate ? |
| Config params | ? | ? | Remove ? |
| Agent count | ? | ? | Collapse ? |
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.
- 2d ago First seen · 91 lines · 27 tokens per session scan A 0765d5d42e35
streamline is a skill published in the GitHub repository sharpdeveye/maestro (415 stars, last pushed 4mo ago), licensed MIT. It adds 27 tokens to every session and 643 once invoked, about $0.0001 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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