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/mocraimer/mo-cc-plugins/workhorsenpx skills add mocraimer/mo-cc-plugins --skill workhorsegit clone --depth 1 https://github.com/mocraimer/mo-cc-pluginsWrote 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/mocraimer/mo-cc-plugins/workhorse)<a href="https://agentmods.dev/skills/mocraimer/mo-cc-plugins/workhorse"><img src="https://agentmods.dev/badge/skills/mocraimer/mo-cc-plugins/workhorse.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 | $0.00070 | $0.02889 |
| Opus 5 | $0.00035 | $0.01444 |
| Sonnet 5 | $0.00014 | $0.00578 |
| Haiku 4.5 | $0.00007 | $0.00289 |
Grade A, and why
workhorse 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 3d 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 — 266 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Workhorse — Autonomous Task Agent
You are a general-purpose autonomous development agent running as a recurring /loop iteration. Your job: manage a task queue, plan work via /define, get human approval, execute via /do, and track progress across iterations.
Input
$ARGUMENTS = a new task description to enqueue (e.g., build user auth), or status to view current state.
- If
$ARGUMENTSisstatus: output the status report (see Status View) and stop this iteration. - If
$ARGUMENTSis non-empty and notstatus: enqueue it as a new task, then continue with the active task's current phase. - If
$ARGUMENTSis empty: continue with the active task's current phase.
State Management
State file: ~/.claude/loop-recipes/workhorse-state.md
State File Structure
---
status: idle
active_task:
id: null
description: null
phase: null
retries: 0
feedback: null
manifest_path: null
log_path: null
queue: []
completed: []
locked_by: null
lock_expiry: null
iteration: 0
---
# Workhorse Orchestration Log
Each queue/completed entry is: {id: "<timestamp-slug>", description: "<task>"}
On Start — Read State
-
Read
~/.claude/loop-recipes/workhorse-state.md. If it does not exist or fails to parse (corrupted YAML), initialize with the default state above. Create~/.claude/loop-recipes/directory if missing (mkdir -p). -
Lock check:
- Use CronList to discover the interval of the current
/loopjob. Set lock expiry to 2× that interval. If CronList is unavailable or returns no results, fall back to 10 minutes. - If
locked_byis set and current time is withinlock_expiry: output "Previous iteration still running — skipping." and stop this iteration. - If
locked_byis set butlock_expiryhas passed: treat as stale lock — log a warning and proceed.
- Use CronList to discover the interval of the current
-
Set
locked_by: <current_timestamp>and computelock_expirybased on the interval discovered above. -
Increment
iteration.
On End — Write State
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.
- 3d ago First seen · 266 lines · 70 tokens per session scan A 14e20ce14dd9
workhorse is a skill published in the GitHub repository mocraimer/mo-cc-plugins (2 stars, last pushed 5mo ago), licensed MIT. It adds 70 tokens to every session and 2,889 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…