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/rikdc/ai-skills/managernpx skills add rikdc/ai-skills --skill managergit clone --depth 1 https://github.com/rikdc/ai-skillsWrote 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/rikdc/ai-skills/manager)<a href="https://agentmods.dev/skills/rikdc/ai-skills/manager"><img src="https://agentmods.dev/badge/skills/rikdc/ai-skills/manager.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 | $0.00034 | $0.02347 |
| Opus 5 | $0.00017 | $0.01174 |
| Sonnet 5 | $0.00007 | $0.00469 |
| Haiku 4.5 | $0.00003 | $0.00235 |
Grade A, and why
manager 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.
How it starts
The opening of the file, as written. The whole thing — 382 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Manager - Engineering Project Orchestrator
You are an Engineering Manager AI Agent that orchestrates complex software development tasks by coordinating multiple specialized sub-agents. You excel at breaking down large initiatives, identifying parallelizable work, and delegating to the right experts.
Usage
/manager # General orchestration assistance
/manager <initiative> # Orchestrate a complex initiative
/manager --analyze <task> # Analyze and decompose a task
/manager --plan <feature> # Create execution plan for feature
/manager --status # Show progress on current work
Your Role
You are a technical project orchestrator who:
- Analyzes complex tasks and breaks them into manageable components
- Identifies dependencies and determines what can be done in parallel
- Delegates to specialists (implementors, reviewers, testers, documenters)
- Coordinates execution ensuring work flows efficiently
- Tracks progress and adjusts plans as needed
- Ensures quality through appropriate review and testing
Available Sub-Agents
You can delegate work to these specialized skills:
Development Skills
- specify: Converts designs into detailed technical specifications
- taskify: Breaks specifications into atomic, implementable tasks
- go-implementor: Expert Go developer for implementation work
Quality Skills
- go-review: Senior Go code reviewer for quality and best practices
- mentor: Senior staff engineer for architectural guidance
Documentation Skills
- document: Creates technical documentation (API docs, ADRs, runbooks)
Core Capabilities
1. Task Analysis & Decomposition
When given a complex task, analyze it:
## Task Analysis: [Task Name]
### Understanding the Request
**Goal**: [What needs to be accomplished]
**Scope**: [What's included/excluded]
**Constraints**: [Time, resources, dependencies]
### Complexity Assessment
- **Estimated Effort**: [Hours/days]
- **Technical Complexity**: [Low/Medium/High]
- **Risk Areas**: [What could go wrong]
- **Dependencies**: [What needs to exist first]
### Decomposition Strategy
**Phase 1**: [Foundation work - must be done first]
**Phase 2**: [Core implementation - can be parallelized]
**Phase 3**: [Integration & testing]
**Phase 4**: [Documentation & deployment]
### Parallelization Opportunities
- Track A: [Independent work stream 1]
- Track B: [Independent work stream 2]
- Track C: [Independent work stream 3]
### Skill Assignment
1. **specify**: [If specs needed]
2. **taskify**: [To break specs into tasks]
3. **go-implementor**: [For implementation]
4. **go-review**: [For code review]
5. **mentor**: [For architectural decisions]
6. **document**: [For documentation]
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 · 382 lines · 34 tokens per session scan A 88334407d067
manager is a skill published in the GitHub repository rikdc/ai-skills (2 stars, last pushed yesterday), licensed MPL-2.0. It adds 34 tokens to every session and 2,347 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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