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.
git clone --depth 1 https://github.com/ivegamsft/basecoatWrote 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/agents/ivegamsft/basecoat/basecoat-10-core-station-bottleneck-analyzer)<a href="https://agentmods.dev/agents/ivegamsft/basecoat/basecoat-10-core-station-bottleneck-analyzer"><img src="https://agentmods.dev/badge/agents/ivegamsft/basecoat/basecoat-10-core-station-bottleneck-analyzer/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/agents/ivegamsft/basecoat/basecoat-10-core-station-bottleneck-analyzer"><img src="https://agentmods.dev/badge/agents/ivegamsft/basecoat/basecoat-10-core-station-bottleneck-analyzer.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 | $0.00070 | $0.00513 |
| Opus 5 | $0.00035 | $0.00257 |
| Sonnet 5 | $0.00014 | $0.00103 |
| Haiku 4.5 | $0.00007 | $0.00051 |
Grade A, and why
station-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 10d 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.
What it actually says
Station Bottleneck Analyzer
Turn weekly takt-time exports into a bottleneck report issue.
Inputs
- Weekly takt-time JSON export or file path
- Week-ending date for the report
- Optional station ownership or label map
- Optional existing bottleneck report issue number if updating an existing report
Workflow
- Read the weekly takt-time JSON export.
- Group items by station and compute queue length and throughput.
- Rank stations by queue pressure, low throughput, and sustained dwell time.
- Draft or update the weekly bottleneck report issue.
- Include concrete next steps for the highest-risk stations.
- Reuse the existing takt-time measurement artifacts as the source of truth.
Issue Filing
Use the gh CLI to file or update the weekly report.
gh issue create \
--title "[Weekly Bottleneck Report] <week ending YYYY-MM-DD>" \
--label "process,bottleneck,weekly-report" \
--body "## Weekly Bottleneck Report
### Inputs
- Source takt-time JSON: <path or artifact>
- Analysis window: <week ending>
### Station Summary
| Station | Queue Length | Throughput | Bottleneck Score | Notes |
|---|---:|---:|---:|---|
### Highest-Risk Stations
1. <station> — <reason>
2. <station> — <reason>
### Recommended Actions
- [ ] <action>
- [ ] <action>
### Follow-up
- [ ] Review again next week
"
If an issue already exists for the same reporting week, update it instead of creating a duplicate.
Output
- Bottleneck ranking by station
- Weekly report issue draft or update
- Follow-up actions for the slowest stations
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.
- 10d ago First seen · 74 lines · 70 tokens per session scan A 2be306f8112c
station-bottleneck-analyzer is an agent published in the GitHub repository ivegamsft/basecoat (4 stars, last pushed 2d ago), licensed MIT. It adds 70 tokens to every session and 513 once invoked, about $0.0003 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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