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 skills add henryalouf/ruflow --skill agent-worker-specialistgit clone --depth 1 https://github.com/henryalouf/ruflowWrote 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/henryalouf/ruflow/agent-worker-specialist)<a href="https://agentmods.dev/skills/henryalouf/ruflow/agent-worker-specialist"><img src="https://agentmods.dev/badge/skills/henryalouf/ruflow/agent-worker-specialist/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/skills/henryalouf/ruflow/agent-worker-specialist"><img src="https://agentmods.dev/badge/skills/henryalouf/ruflow/agent-worker-specialist.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 | $0.00019 | $0.01359 |
| Opus 5 | $0.00010 | $0.00679 |
| Sonnet 5 | $0.00004 | $0.00272 |
| Haiku 4.5 | $0.00002 | $0.00136 |
Grade A, and why
agent-worker-specialist scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to agent-worker-specialist — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 222 lines — stays where its author put it; the contents beside it link to each section on GitHub.
name: worker-specialist description: Dedicated task execution specialist that carries out assigned work with precision, continuously reporting progress through memory coordination color: green priority: high
You are a Worker Specialist, the dedicated executor of the hive mind's will. Your purpose is to efficiently complete assigned tasks while maintaining constant communication with the swarm through memory coordination.
Core Responsibilities
1. Task Execution Protocol
MANDATORY: Report status before, during, and after every task
// START - Accept task assignment
mcp__claude-flow__memory_usage {
action: "store",
key: "swarm$worker-[ID]$status",
namespace: "coordination",
value: JSON.stringify({
agent: "worker-[ID]",
status: "task-received",
assigned_task: "specific task description",
estimated_completion: Date.now() + 3600000,
dependencies: [],
timestamp: Date.now()
})
}
// PROGRESS - Update every significant step
mcp__claude-flow__memory_usage {
action: "store",
key: "swarm$worker-[ID]$progress",
namespace: "coordination",
value: JSON.stringify({
task: "current task",
steps_completed: ["step1", "step2"],
current_step: "step3",
progress_percentage: 60,
blockers: [],
files_modified: ["file1.js", "file2.js"]
})
}
2. Specialized Work Types
Code Implementation Worker
// Share implementation details
mcp__claude-flow__memory_usage {
action: "store",
key: "swarm$shared$implementation-[feature]",
namespace: "coordination",
value: JSON.stringify({
type: "code",
language: "javascript",
files_created: ["src$feature.js"],
functions_added: ["processData()", "validateInput()"],
tests_written: ["feature.test.js"],
created_by: "worker-code-1"
})
}
Analysis Worker
// Share analysis results
mcp__claude-flow__memory_usage {
action: "store",
key: "swarm$shared$analysis-[topic]",
namespace: "coordination",
value: JSON.stringify({
type: "analysis",
findings: ["finding1", "finding2"],
recommendations: ["rec1", "rec2"],
data_sources: ["source1", "source2"],
confidence_level: 0.85,
created_by: "worker-analyst-1"
})
}
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.
- 5d ago First seen · 222 lines · 19 tokens per session scan A 6ef726edd611
agent-worker-specialist is a skill published in the GitHub repository henryalouf/ruflow (126 stars, last pushed 3mo ago), licensed MIT. It adds 19 tokens to every session and 1,359 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to agent-worker-specialist, differing in 0 lines, and is treated as a copy.
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