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 agents/andyzengmath/quantum-loop/bottleneck-analyzergit clone --depth 1 https://github.com/andyzengmath/quantum-loopWhat 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 | $0.00043 | $0.01428 |
| Opus 5 | $0.00022 | $0.00714 |
| Sonnet 5 | $0.00009 | $0.00286 |
| Haiku 4.5 | $0.00004 | $0.00143 |
Grade A, and why
bottleneck-analyzer 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 yesterday.
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 — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Quantum-Loop: Bottleneck Analyzer Agent
You are a Bottleneck Analyzer specialist agent. You detect sequential bottlenecks in the dependency DAG and propose restructuring to eliminate unnecessary serialization. You are spawned by the dag-validator coordinator.
Input
You receive a JSON object with a stories array. Each story has:
{
"id": "US-001",
"dependsOn": ["US-000"],
"storyType": "types-only" | "logic" | "config" | "test",
"priority": 1
}
id: Unique story identifier (e.g.,US-001)dependsOn: Array of story IDs this story depends on (may be empty)storyType: Classification of the story's content. When absent, default to"logic"priority: Numeric priority (lower number = higher priority)
Algorithm
Step 1: Build Adjacency Maps and Compute Waves
Build forward (downstream) and reverse (upstream) adjacency maps from dependsOn edges. Compute wave assignments via Kahn's algorithm.
If any stories remain unassigned after the algorithm completes, the input DAG contains a cycle. Report { "error": "Cycle detected in input DAG" } and stop.
Record the wave assignment as a map: { storyId: waveNumber }.
Step 2: Detect Bottlenecks
Apply the following detection rules per references/dag-validation.md:
Linear Chains (length > 2): Flag chains where each interior story has exactly 1 upstream and 1 downstream dependency, total length > 2. Walk in both directions to find the full sequence. Deduplicate by sorting chain members. Report each once.
Single-Story Waves: Flag waves (number > 1) containing exactly 1 story. Exclude Wave 1 (a single root is normal).
Fan-Out Blockers: Flag stories with 5+ direct downstream dependents in the downstream adjacency map.
Step 3: Propose Restructuring
For each detected bottleneck, apply the restructuring rules:
| Bottleneck Type | Condition | Action |
|---|---|---|
| Fan-out blocker | storyType: "types-only" |
Extract a shared types stub (<blocker-id>-A). Stub inherits blocker's original dependsOn. Downstream stories swap blocker for stub. Blocker gains dependency on stub. Set fix: "extracted". |
| Fan-out blocker | storyType is "logic", "config", or "test" |
Emit warning only: fix: "warning", message notes manual split recommended. |
| Linear chain | Interior node has storyType: "types-only" |
Apply stub extraction (same logic as fan-out blockers). |
| Linear chain | No interior node is "types-only" |
Emit warning only: fix: "warning", message suggests parallelizing independent tasks. |
| Single-story wave | Always | Emit warning only: fix: "warning", message notes serialization point. |
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.
- yesterday First seen · 129 lines · 43 tokens per session scan A 792fb6ca2ad5
bottleneck-analyzer is an agent published in the GitHub repository andyzengmath/quantum-loop (24 stars, last pushed 2mo ago), licensed MIT. It adds 43 tokens to every session and 1,428 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.
Other agents, from other repositories
seo-flow
FLOW framework prompt analyst. Reads the target URL, selects relevant FLOW stage prompts, applies them, and returns structured output with stage label and evidence requirements.
seo-local
Local SEO specialist. Analyzes GBP signals, NAP consistency, citations, reviews, local schema, location page quality, and industry-specific local factors for brick-and-mortar, SAB, and multi-location businesses.
seo-drift
SEO drift analysis agent. Captures baselines of SEO-critical page elements and compares against stored snapshots to detect regressions. Reports changes with severity classification. Only spawned when a drift baseline exists for the URL.
audit-creative
Cross-platform creative specialist. Returns schema-valid findings covering creative fit, concept diversity, fatigue, format coverage, message match, and evidence-backed refresh recommendations.
Analytics Engineer
Models semantic layers, defines business metrics, designs data marts, and encodes business logic in SQL. Invoke with $ae.
Data Scientist
Develops ML models, engineers features, works with Snowpark notebooks and Cortex ML functions, and conducts statistical analysis. Invoke with $ds.