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/cass-2003/local-workflow-skill/capacity-plannernpx skills add cass-2003/local-workflow-skill --skill capacity-plannergit clone --depth 1 https://github.com/cass-2003/local-workflow-skillWrote 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/cass-2003/local-workflow-skill/capacity-planner)<a href="https://agentmods.dev/skills/cass-2003/local-workflow-skill/capacity-planner"><img src="https://agentmods.dev/badge/skills/cass-2003/local-workflow-skill/capacity-planner.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 5.1 | $0.00166 | $0.03068 |
| Opus 5 | $0.00083 | $0.01534 |
| Sonnet 5 | $0.00033 | $0.00614 |
| Haiku 4.5 | $0.00017 | $0.00307 |
Grade A, and why
capacity-planner 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 6d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- capacity-planner — 95% identical, 7 lines differ
How it starts
The opening of the file, as written. The whole thing — 257 lines — stays where its author put it; the contents beside it link to each section on GitHub.
capacity-planner
Sizing tool for ops teams that handle queued work — Support, CX, Customer Success, BizOps, IT ops, Finance ops. Built on Erlang-C queueing theory, Little's Law, and the operational-leadership canon (Fournier, Larson, Cleveland, Reinertsen). Deterministic, stdlib-only, no LLM calls.
Purpose
You are an ops leader sized 15 → 35 with no idea how the 35-person org will actually behave at peak load. Or you are at 88% utilization and SLA is starting to slip. Or you have a hiring budget approved and need to sequence it across four quarters without burning out the existing team. This skill answers those questions with arithmetic, not vibes.
It produces three artifacts:
- Capacity sizing at 70/80/90% utilization against P50/P90/P99 demand, with P(SLA breach) at each point and a SAFE/WATCH/AT_RISK/CRITICAL risk band.
- Utilization health at the per-member traffic-light level plus a team verdict (HEALTHY/SQUEEZED/OVERLOADED/UNBALANCED).
- 12-month quarterly hiring plan accounting for ramp curves, attrition, QoQ demand growth, and span-of-control manager triggers.
When to use
- Annual ops capacity planning (October-November for the following fiscal year).
- Quarterly re-sizing if demand changed >15% or attrition spiked.
- Pre-budget defense — the math that justifies the headcount ask to your CFO.
- Diagnostic when an ops team is missing SLA and you need to know whether it's a sizing problem, a process problem, or a bottleneck problem.
- M&A / new-segment launch modeling — sizing a new team or combined org.
Workflow
- Intake demand. Pull P50/P90/P99 daily ticket/case volume from your work system (Zendesk, Intercom, JSM, ServiceNow, Salesforce). If you only have averages, stop and pull the distribution. Single- point demand estimates are the most expensive anti-pattern in ops.
- Model throughput. Run
capacity_modeler.pywith your demand, AHT, SLA target, current FTE, and shrinkage. Use--profilefor your function (support / cx / bizops / finance-ops / it-ops). Read the 80%-utilization row — that's your sizing point. - Flag utilization risk. Run
utilization_analyzer.pyagainst your current team's actual utilization data. Anyone >85% sustained is a throughput-collapse risk per Reinertsen. Spread >30 percentage points across team means UNBALANCED — fix that before hiring. - Sequence hiring. Run
hiring_sequencer.pywith current FTE, target EOY, ramp time, attrition, and growth. It will front-load hires (Q1 35%, Q4 15%), apply ramp curves, and trigger a manager hire when span of control crosses 7 ICs/manager. - Walk the Forcing-question library (see below). One question at a time. Do not skip ahead. Answers must be written down before you commit the plan.
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- assets/capacity_brief_template.md 4.9 KB
- references/capacity_anti_patterns.md 8.8 KB
- references/ops_workforce_planning_canon.md 6.2 KB
- references/queueing_theory_canon.md 5.8 KB
- scripts/capacity_modeler.py 16 KB runs code
- scripts/hiring_sequencer.py 12 KB runs code
- scripts/utilization_analyzer.py 9.7 KB runs code
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.
- 6d ago First seen · 257 lines · 166 tokens per session scan A 314fec4e0575
capacity-planner is a skill published in the GitHub repository cass-2003/local-workflow-skill (12 stars, last pushed 1mo ago), licensed MIT. It adds 166 tokens to every session and 3,068 once invoked, about $0.0008 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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