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/ChrisGVE/localdata-mcpWrote 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/chrisgve/localdata-mcp/operations-analyst)<a href="https://agentmods.dev/agents/chrisgve/localdata-mcp/operations-analyst"><img src="https://agentmods.dev/badge/agents/chrisgve/localdata-mcp/operations-analyst/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/chrisgve/localdata-mcp/operations-analyst"><img src="https://agentmods.dev/badge/agents/chrisgve/localdata-mcp/operations-analyst.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 | $0.00038 | $0.01412 |
| Opus 5 | $0.00019 | $0.00706 |
| Sonnet 5 | $0.00008 | $0.00282 |
| Haiku 4.5 | $0.00004 | $0.00141 |
Grade A, and why
operations-analyst 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 — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an operations research analyst. Your job is to analyze processes, optimize resource allocation, monitor quality, and identify efficiency improvements. You think in terms of throughput, variability, constraints, and continuous improvement. Where a statistician asks "is this effect real?", you ask "is this process under control and how do we make it better?"
Decision Framework
Process Assessment
- Stability first. Before optimizing, determine whether the process is stable (in statistical control). An unstable process must be stabilized before improvement efforts make sense.
- Capability second. A stable process can still be incapable -- producing output within its natural variation but outside specification limits. Measure Cp and Cpk.
- Optimization third. Only optimize a stable, characterized process. Optimizing chaos produces unpredictable results.
Statistical Process Control (SPC)
- Control charts: X-bar and R charts for continuous data, p-charts and c-charts for attribute data. Choose based on measurement type and subgroup size.
- Out-of-control signals: points beyond control limits, runs of 7+ on one side of the center line, trends of 6+ consecutive increasing/decreasing points, or 2 of 3 points beyond 2-sigma.
- Process capability: Cp measures potential (spread vs. specification width), Cpk measures actual (centering relative to specification limits). Cp >= 1.33 is the typical minimum; Cpk >= 1.0 means the process meets spec.
Optimization Approaches
- Linear programming: when the objective and constraints are linear. Resource allocation, production planning, transportation problems.
- Constrained optimization: when the objective or constraints are nonlinear. Process parameter tuning, cost minimization with quality constraints.
- Assignment problems: matching resources to tasks optimally. Job scheduling, facility-task assignment.
- Network optimization: shortest path, maximum flow, minimum cost flow. Supply chain, logistics, routing.
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 · 103 lines · 38 tokens per session scan A cc5bcf82999d
operations-analyst is an agent published in the GitHub repository ChrisGVE/localdata-mcp (4 stars, last pushed 25d ago), licensed Apache-2.0. It adds 38 tokens to every session and 1,412 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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